{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/rvwielen/Library/CloudStorage/Dropbox/HouseBirthplaceProject/Paper/PSRM/FINAL_ReplicationMaterials/ReplicationMaterials_Submitted/ReplicationLog_Final.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 5 Aug 2024, 07:10:26

{com}. do "/Users/rvwielen/Library/CloudStorage/Dropbox/HouseBirthplaceProject/Paper/PSRM/FINAL_ReplicationMaterials/ReplicationMaterials_Submitted/Code_HouseBirthplace_PSRM.do"
{txt}
{com}. ************************************
. *Table 1 - Members' Places of Birth 
. ************************************
. 
. *Select directory
. use "House_BirthplaceData.dta"
{txt}
{com}. 
. *Column 1
. bysort congress: count if born_indist==0

{txt}{hline}
-> congress = 107
  {res}209
{txt}{hline}
-> congress = 108
  {res}217
{txt}{hline}
-> congress = 109
  {res}230
{txt}{hline}
-> congress = 110
  {res}239
{txt}{hline}
-> congress = 111
  {res}247
{txt}{hline}
-> congress = 112
  {res}251
{txt}{hline}
-> congress = 113
  {res}257
{txt}{hline}
-> congress = 114
  {res}257
{txt}{hline}
-> congress = 115
  {res}271
{txt}
{com}. *Column 2
. bysort congress: count if born_instate==0

{txt}{hline}
-> congress = 107
  {res}143
{txt}{hline}
-> congress = 108
  {res}149
{txt}{hline}
-> congress = 109
  {res}150
{txt}{hline}
-> congress = 110
  {res}156
{txt}{hline}
-> congress = 111
  {res}165
{txt}{hline}
-> congress = 112
  {res}168
{txt}{hline}
-> congress = 113
  {res}170
{txt}{hline}
-> congress = 114
  {res}165
{txt}{hline}
-> congress = 115
  {res}180
{txt}
{com}. *Column 3
. bysort congress: count if born_inregion==0

{txt}{hline}
-> congress = 107
  {res}108
{txt}{hline}
-> congress = 108
  {res}115
{txt}{hline}
-> congress = 109
  {res}114
{txt}{hline}
-> congress = 110
  {res}120
{txt}{hline}
-> congress = 111
  {res}130
{txt}{hline}
-> congress = 112
  {res}126
{txt}{hline}
-> congress = 113
  {res}128
{txt}{hline}
-> congress = 114
  {res}124
{txt}{hline}
-> congress = 115
  {res}137
{txt}
{com}. *Column 4
. bysort congress: count if birth_Abroad==1 | birthstateabbrev=="DC"

{txt}{hline}
-> congress = 107
  {res}12
{txt}{hline}
-> congress = 108
  {res}13
{txt}{hline}
-> congress = 109
  {res}14
{txt}{hline}
-> congress = 110
  {res}18
{txt}{hline}
-> congress = 111
  {res}21
{txt}{hline}
-> congress = 112
  {res}18
{txt}{hline}
-> congress = 113
  {res}19
{txt}{hline}
-> congress = 114
  {res}23
{txt}{hline}
-> congress = 115
  {res}32
{txt}
{com}. 
. clear
{txt}
{com}. 
. 
. *************************
. *Table 2 - Balance Test 
. *************************
. 
. *Select directory
. use "House_BirthplaceData.dta"
{txt}
{com}. 
. duplicates drop icpsr_id, force

{p 0 4}{txt}Duplicates in terms of {res} icpsr_id{p_end}

{txt}(3,004 observations deleted)

{com}. 
. *BORN IN-STATE (Top rows of Table 2)
. 
. *All members - Column 1
. logit born_instate AgeInteger Female Black Hispanic dpres i.birthstate_icpsr i.Rep_state_icpsr if congress<116

{txt}note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 2 obs not used

note: 64.birthstate_icpsr != 0 predicts success perfectly
      64.birthstate_icpsr dropped and 2 obs not used

note: 82.birthstate_icpsr != 0 predicts success perfectly
      82.birthstate_icpsr dropped and 4 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 12 obs not used

note: 99.birthstate_icpsr != 0 predicts failure perfectly
      99.birthstate_icpsr dropped and 1 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 2 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 3 obs not used

note: 102.birthstate_icpsr != 0 predicts failure perfectly
      102.birthstate_icpsr dropped and 1 obs not used

note: 103.birthstate_icpsr != 0 predicts failure perfectly
      103.birthstate_icpsr dropped and 1 obs not used

note: 104.birthstate_icpsr != 0 predicts failure perfectly
      104.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 2 obs not used

note: 106.birthstate_icpsr != 0 predicts failure perfectly
      106.birthstate_icpsr dropped and 1 obs not used

note: 107.birthstate_icpsr != 0 predicts failure perfectly
      107.birthstate_icpsr dropped and 1 obs not used

note: 108.birthstate_icpsr != 0 predicts failure perfectly
      108.birthstate_icpsr dropped and 2 obs not used

note: 109.birthstate_icpsr != 0 predicts failure perfectly
      109.birthstate_icpsr dropped and 1 obs not used

note: 110.birthstate_icpsr != 0 predicts failure perfectly
      110.birthstate_icpsr dropped and 2 obs not used

note: 111.birthstate_icpsr != 0 predicts failure perfectly
      111.birthstate_icpsr dropped and 4 obs not used

note: 112.birthstate_icpsr != 0 predicts failure perfectly
      112.birthstate_icpsr dropped and 1 obs not used

note: 113.birthstate_icpsr != 0 predicts failure perfectly
      113.birthstate_icpsr dropped and 1 obs not used

note: 114.birthstate_icpsr != 0 predicts failure perfectly
      114.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 3 obs not used

note: 116.birthstate_icpsr != 0 predicts failure perfectly
      116.birthstate_icpsr dropped and 2 obs not used

note: 117.birthstate_icpsr != 0 predicts failure perfectly
      117.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 2 obs not used

note: 6.Rep_state_icpsr != 0 predicts failure perfectly
      6.Rep_state_icpsr dropped and 2 obs not used

note: 11.Rep_state_icpsr != 0 predicts failure perfectly
      11.Rep_state_icpsr dropped and 1 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 3 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 6 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 5 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 5 obs not used

note: 64.Rep_state_icpsr != 0 predicts failure perfectly
      64.Rep_state_icpsr dropped and 2 obs not used

note: 81.Rep_state_icpsr != 0 predicts failure perfectly
      81.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 2 obs not used

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-578.18564}  
Iteration 1:{space 3}log likelihood = {res:-422.09296}  
Iteration 2:{space 3}log likelihood = {res:-418.69599}  
Iteration 3:{space 3}log likelihood = {res:-418.64722}  
Iteration 4:{space 3}log likelihood = {res: -418.6472}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       908
{txt}{col 49}LR chi2({res}89{txt}){col 67}= {res}    319.08
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res} -418.6472{txt}{col 49}Pseudo R2{col 67}= {res}    0.2759

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    born_instate{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}AgeInteger {c |}{col 18}{res}{space 2}-.0119486{col 30}{space 2} .0096513{col 41}{space 1}   -1.24{col 50}{space 3}0.216{col 58}{space 4}-.0308648{col 71}{space 3} .0069676
{txt}{space 10}Female {c |}{col 18}{res}{space 2}-.3484972{col 30}{space 2} .2652512{col 41}{space 1}   -1.31{col 50}{space 3}0.189{col 58}{space 4}  -.86838{col 71}{space 3} .1713856
{txt}{space 11}Black {c |}{col 18}{res}{space 2}-.3555684{col 30}{space 2} .4168902{col 41}{space 1}   -0.85{col 50}{space 3}0.394{col 58}{space 4}-1.172658{col 71}{space 3} .4615214
{txt}{space 8}Hispanic {c |}{col 18}{res}{space 2}   .66889{col 30}{space 2} .5409792{col 41}{space 1}    1.24{col 50}{space 3}0.216{col 58}{space 4}-.3914097{col 71}{space 3}  1.72919
{txt}{space 11}dpres {c |}{col 18}{res}{space 2} .0133388{col 30}{space 2}  .009982{col 41}{space 1}    1.34{col 50}{space 3}0.181{col 58}{space 4}-.0062256{col 71}{space 3} .0329032
{txt}{space 16} {c |}
birthstate_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2} 2.860954{col 30}{space 2} 2.248418{col 41}{space 1}    1.27{col 50}{space 3}0.203{col 58}{space 4}-1.545864{col 71}{space 3} 7.267771
{txt}{space 14}3  {c |}{col 18}{res}{space 2}-.8047917{col 30}{space 2} 1.050725{col 41}{space 1}   -0.77{col 50}{space 3}0.444{col 58}{space 4}-2.864175{col 71}{space 3} 1.254592
{txt}{space 14}4  {c |}{col 18}{res}{space 2} 4.016973{col 30}{space 2} 1.977687{col 41}{space 1}    2.03{col 50}{space 3}0.042{col 58}{space 4} .1407781{col 71}{space 3} 7.893167
{txt}{space 14}5  {c |}{col 18}{res}{space 2}-1.206815{col 30}{space 2} 1.935897{col 41}{space 1}   -0.62{col 50}{space 3}0.533{col 58}{space 4}-5.001103{col 71}{space 3} 2.587474
{txt}{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2} 1.169487{col 30}{space 2} 1.076273{col 41}{space 1}    1.09{col 50}{space 3}0.277{col 58}{space 4}-.9399682{col 71}{space 3} 3.278943
{txt}{space 13}13  {c |}{col 18}{res}{space 2}-.4874568{col 30}{space 2}  .959829{col 41}{space 1}   -0.51{col 50}{space 3}0.612{col 58}{space 4}-2.368687{col 71}{space 3} 1.393773
{txt}{space 13}14  {c |}{col 18}{res}{space 2}-.3327363{col 30}{space 2} 1.029909{col 41}{space 1}   -0.32{col 50}{space 3}0.747{col 58}{space 4} -2.35132{col 71}{space 3} 1.685848
{txt}{space 13}21  {c |}{col 18}{res}{space 2}-.3705743{col 30}{space 2} 1.002511{col 41}{space 1}   -0.37{col 50}{space 3}0.712{col 58}{space 4}-2.335461{col 71}{space 3} 1.594312
{txt}{space 13}22  {c |}{col 18}{res}{space 2} 1.161205{col 30}{space 2} 1.206765{col 41}{space 1}    0.96{col 50}{space 3}0.336{col 58}{space 4}-1.204012{col 71}{space 3} 3.526421
{txt}{space 13}23  {c |}{col 18}{res}{space 2} .2551865{col 30}{space 2} 1.024851{col 41}{space 1}    0.25{col 50}{space 3}0.803{col 58}{space 4}-1.753485{col 71}{space 3} 2.263858
{txt}{space 13}24  {c |}{col 18}{res}{space 2}-.6072314{col 30}{space 2} 1.245948{col 41}{space 1}   -0.49{col 50}{space 3}0.626{col 58}{space 4}-3.049245{col 71}{space 3} 1.834782
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{txt}{space 13}31  {c |}{col 18}{res}{space 2}-2.564352{col 30}{space 2} 1.483401{col 41}{space 1}   -1.73{col 50}{space 3}0.084{col 58}{space 4}-5.471765{col 71}{space 3} .3430605
{txt}{space 13}32  {c |}{col 18}{res}{space 2} 4.915477{col 30}{space 2} 2.002841{col 41}{space 1}    2.45{col 50}{space 3}0.014{col 58}{space 4} .9899807{col 71}{space 3} 8.840974
{txt}{space 13}33  {c |}{col 18}{res}{space 2}-.3025918{col 30}{space 2} 1.163972{col 41}{space 1}   -0.26{col 50}{space 3}0.795{col 58}{space 4}-2.583934{col 71}{space 3}  1.97875
{txt}{space 13}34  {c |}{col 18}{res}{space 2} .1654896{col 30}{space 2}  1.23386{col 41}{space 1}    0.13{col 50}{space 3}0.893{col 58}{space 4}-2.252832{col 71}{space 3} 2.583811
{txt}{space 13}35  {c |}{col 18}{res}{space 2} .8644995{col 30}{space 2} 1.599439{col 41}{space 1}    0.54{col 50}{space 3}0.589{col 58}{space 4}-2.270344{col 71}{space 3} 3.999343
{txt}{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
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{txt}{space 13}47  {c |}{col 18}{res}{space 2} .7364596{col 30}{space 2} 1.133682{col 41}{space 1}    0.65{col 50}{space 3}0.516{col 58}{space 4}-1.485517{col 71}{space 3} 2.958436
{txt}{space 13}48  {c |}{col 18}{res}{space 2} .6929608{col 30}{space 2} 1.405423{col 41}{space 1}    0.49{col 50}{space 3}0.622{col 58}{space 4}-2.061618{col 71}{space 3} 3.447539
{txt}{space 13}49  {c |}{col 18}{res}{space 2} 2.763404{col 30}{space 2} 1.103253{col 41}{space 1}    2.50{col 50}{space 3}0.012{col 58}{space 4} .6010685{col 71}{space 3}  4.92574
{txt}{space 13}51  {c |}{col 18}{res}{space 2}-.7265734{col 30}{space 2}  1.43257{col 41}{space 1}   -0.51{col 50}{space 3}0.612{col 58}{space 4}-3.534359{col 71}{space 3} 2.081212
{txt}{space 13}52  {c |}{col 18}{res}{space 2} .5585079{col 30}{space 2} 1.187752{col 41}{space 1}    0.47{col 50}{space 3}0.638{col 58}{space 4}-1.769444{col 71}{space 3} 2.886459
{txt}{space 13}53  {c |}{col 18}{res}{space 2} 2.615742{col 30}{space 2} 1.243504{col 41}{space 1}    2.10{col 50}{space 3}0.035{col 58}{space 4} .1785183{col 71}{space 3} 5.052966
{txt}{space 13}54  {c |}{col 18}{res}{space 2} .1916312{col 30}{space 2} 1.225101{col 41}{space 1}    0.16{col 50}{space 3}0.876{col 58}{space 4}-2.209522{col 71}{space 3} 2.592784
{txt}{space 13}56  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
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{txt}{space 13}62  {c |}{col 18}{res}{space 2} 3.461132{col 30}{space 2} 1.472367{col 41}{space 1}    2.35{col 50}{space 3}0.019{col 58}{space 4} .5753448{col 71}{space 3} 6.346919
{txt}{space 13}63  {c |}{col 18}{res}{space 2} 2.688368{col 30}{space 2}  1.82112{col 41}{space 1}    1.48{col 50}{space 3}0.140{col 58}{space 4}-.8809609{col 71}{space 3} 6.257697
{txt}{space 13}64  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
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{txt}{space 13}66  {c |}{col 18}{res}{space 2} 2.178882{col 30}{space 2} 1.357032{col 41}{space 1}    1.61{col 50}{space 3}0.108{col 58}{space 4}-.4808528{col 71}{space 3} 4.838616
{txt}{space 13}67  {c |}{col 18}{res}{space 2} 4.546926{col 30}{space 2} 2.067072{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .4955402{col 71}{space 3} 8.598312
{txt}{space 13}68  {c |}{col 18}{res}{space 2} 1.098763{col 30}{space 2} 1.840278{col 41}{space 1}    0.60{col 50}{space 3}0.550{col 58}{space 4}-2.508116{col 71}{space 3} 4.705641
{txt}{space 13}71  {c |}{col 18}{res}{space 2} 3.753301{col 30}{space 2} 1.055823{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4} 1.683925{col 71}{space 3} 5.822677
{txt}{space 13}72  {c |}{col 18}{res}{space 2} .6602072{col 30}{space 2} 1.442894{col 41}{space 1}    0.46{col 50}{space 3}0.647{col 58}{space 4}-2.167813{col 71}{space 3} 3.488227
{txt}{space 13}73  {c |}{col 18}{res}{space 2} 1.697182{col 30}{space 2} 1.174986{col 41}{space 1}    1.44{col 50}{space 3}0.149{col 58}{space 4} -.605748{col 71}{space 3} 4.000112
{txt}{space 13}82  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}98  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}99  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}100  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}101  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}102  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}103  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}104  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}105  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}106  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}107  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}108  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}109  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}110  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}111  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}112  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}113  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}114  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}115  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}116  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}117  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}118  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 1}Rep_state_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2}-.4179628{col 30}{space 2} 2.086755{col 41}{space 1}   -0.20{col 50}{space 3}0.841{col 58}{space 4}-4.507927{col 71}{space 3} 3.672001
{txt}{space 14}3  {c |}{col 18}{res}{space 2} 1.413427{col 30}{space 2} 1.103734{col 41}{space 1}    1.28{col 50}{space 3}0.200{col 58}{space 4}-.7498515{col 71}{space 3} 3.576706
{txt}{space 14}4  {c |}{col 18}{res}{space 2}-3.795512{col 30}{space 2} 1.831263{col 41}{space 1}   -2.07{col 50}{space 3}0.038{col 58}{space 4}-7.384722{col 71}{space 3}-.2063014
{txt}{space 14}5  {c |}{col 18}{res}{space 2} 1.337805{col 30}{space 2} 1.937898{col 41}{space 1}    0.69{col 50}{space 3}0.490{col 58}{space 4}-2.460405{col 71}{space 3} 5.136015
{txt}{space 14}6  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2}-.0699356{col 30}{space 2} 1.017513{col 41}{space 1}   -0.07{col 50}{space 3}0.945{col 58}{space 4}-2.064225{col 71}{space 3} 1.924353
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{txt}{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
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{txt}{space 13}42  {c |}{col 18}{res}{space 2}-.5653856{col 30}{space 2} 1.321388{col 41}{space 1}   -0.43{col 50}{space 3}0.669{col 58}{space 4}-3.155258{col 71}{space 3} 2.024487
{txt}{space 13}43  {c |}{col 18}{res}{space 2}-2.165318{col 30}{space 2} .9562508{col 41}{space 1}   -2.26{col 50}{space 3}0.024{col 58}{space 4}-4.039535{col 71}{space 3} -.291101
{txt}{space 13}44  {c |}{col 18}{res}{space 2} -.376192{col 30}{space 2} 1.053941{col 41}{space 1}   -0.36{col 50}{space 3}0.721{col 58}{space 4}-2.441878{col 71}{space 3} 1.689494
{txt}{space 13}45  {c |}{col 18}{res}{space 2} 4.358504{col 30}{space 2} 1.707792{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} 1.011293{col 71}{space 3} 7.705715
{txt}{space 13}46  {c |}{col 18}{res}{space 2} 4.852197{col 30}{space 2} 2.436271{col 41}{space 1}    1.99{col 50}{space 3}0.046{col 58}{space 4} .0771935{col 71}{space 3}   9.6272
{txt}{space 13}47  {c |}{col 18}{res}{space 2} .1068807{col 30}{space 2}  1.07323{col 41}{space 1}    0.10{col 50}{space 3}0.921{col 58}{space 4}-1.996611{col 71}{space 3} 2.210372
{txt}{space 13}48  {c |}{col 18}{res}{space 2}  .352691{col 30}{space 2} 1.383169{col 41}{space 1}    0.25{col 50}{space 3}0.799{col 58}{space 4} -2.35827{col 71}{space 3} 3.063652
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{space 13}61  {c |}{col 18}{res}{space 2}-2.982028{col 30}{space 2} 1.168474{col 41}{space 1}   -2.55{col 50}{space 3}0.011{col 58}{space 4}-5.272196{col 71}{space 3}  -.69186
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{txt}{space 13}64  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
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{txt}{space 13}71  {c |}{col 18}{res}{space 2}-2.238101{col 30}{space 2} .9593952{col 41}{space 1}   -2.33{col 50}{space 3}0.020{col 58}{space 4}-4.118481{col 71}{space 3}-.3577206
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{txt}{space 13}73  {c |}{col 18}{res}{space 2}-.9437644{col 30}{space 2} 1.150467{col 41}{space 1}   -0.82{col 50}{space 3}0.412{col 58}{space 4}-3.198639{col 71}{space 3}  1.31111
{txt}{space 13}81  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}82  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .0261499{col 30}{space 2} 1.147123{col 41}{space 1}    0.02{col 50}{space 3}0.982{col 58}{space 4}-2.222171{col 71}{space 3}  2.27447
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    7.89
{txt}{col 10}Prob > chi2 =  {res}  0.1622
{txt}
{com}. 
. *All members - Column 2
. logit born_instate AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.birthstate_icpsr i.Rep_state_icpsr if congress<116

{txt}note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 2 obs not used

note: 64.birthstate_icpsr != 0 predicts success perfectly
      64.birthstate_icpsr dropped and 2 obs not used

note: 82.birthstate_icpsr != 0 predicts success perfectly
      82.birthstate_icpsr dropped and 4 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 12 obs not used

note: 99.birthstate_icpsr != 0 predicts failure perfectly
      99.birthstate_icpsr dropped and 1 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 2 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 3 obs not used

note: 102.birthstate_icpsr != 0 predicts failure perfectly
      102.birthstate_icpsr dropped and 1 obs not used

note: 103.birthstate_icpsr != 0 predicts failure perfectly
      103.birthstate_icpsr dropped and 1 obs not used

note: 104.birthstate_icpsr != 0 predicts failure perfectly
      104.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 2 obs not used

note: 106.birthstate_icpsr != 0 predicts failure perfectly
      106.birthstate_icpsr dropped and 1 obs not used

note: 107.birthstate_icpsr != 0 predicts failure perfectly
      107.birthstate_icpsr dropped and 1 obs not used

note: 108.birthstate_icpsr != 0 predicts failure perfectly
      108.birthstate_icpsr dropped and 2 obs not used

note: 109.birthstate_icpsr != 0 predicts failure perfectly
      109.birthstate_icpsr dropped and 1 obs not used

note: 110.birthstate_icpsr != 0 predicts failure perfectly
      110.birthstate_icpsr dropped and 2 obs not used

note: 111.birthstate_icpsr != 0 predicts failure perfectly
      111.birthstate_icpsr dropped and 4 obs not used

note: 112.birthstate_icpsr != 0 predicts failure perfectly
      112.birthstate_icpsr dropped and 1 obs not used

note: 113.birthstate_icpsr != 0 predicts failure perfectly
      113.birthstate_icpsr dropped and 1 obs not used

note: 114.birthstate_icpsr != 0 predicts failure perfectly
      114.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 3 obs not used

note: 116.birthstate_icpsr != 0 predicts failure perfectly
      116.birthstate_icpsr dropped and 2 obs not used

note: 117.birthstate_icpsr != 0 predicts failure perfectly
      117.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 2 obs not used

note: 6.Rep_state_icpsr != 0 predicts failure perfectly
      6.Rep_state_icpsr dropped and 2 obs not used

note: 11.Rep_state_icpsr != 0 predicts failure perfectly
      11.Rep_state_icpsr dropped and 1 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 3 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 6 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 5 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 5 obs not used

note: 64.Rep_state_icpsr != 0 predicts failure perfectly
      64.Rep_state_icpsr dropped and 2 obs not used

note: 81.Rep_state_icpsr != 0 predicts failure perfectly
      81.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 2 obs not used

{res}{txt}Iteration 0:{space 3}log likelihood = {res:-577.77935}  
Iteration 1:{space 3}log likelihood = {res:-420.38882}  
Iteration 2:{space 3}log likelihood = {res:-416.99277}  
Iteration 3:{space 3}log likelihood = {res: -416.9474}  
Iteration 4:{space 3}log likelihood = {res:-416.94738}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       907
{txt}{col 49}LR chi2({res}91{txt}){col 67}= {res}    321.66
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-416.94738{txt}{col 49}Pseudo R2{col 67}= {res}    0.2784

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      born_instate{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0197063{col 32}{space 2} .0109623{col 43}{space 1}   -1.80{col 52}{space 3}0.072{col 60}{space 4}-.0411921{col 73}{space 3} .0017795
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.3268242{col 32}{space 2} .2722272{col 43}{space 1}   -1.20{col 52}{space 3}0.230{col 60}{space 4}-.8603796{col 73}{space 3} .2067312
{txt}{space 13}Black {c |}{col 20}{res}{space 2}-.3551234{col 32}{space 2} .4208043{col 43}{space 1}   -0.84{col 52}{space 3}0.399{col 60}{space 4}-1.179885{col 73}{space 3} .4696378
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .6224752{col 32}{space 2} .5472959{col 43}{space 1}    1.14{col 52}{space 3}0.255{col 60}{space 4} -.450205{col 73}{space 3} 1.695155
{txt}{space 13}dpres {c |}{col 20}{res}{space 2} .0063713{col 32}{space 2} .0117743{col 43}{space 1}    0.54{col 52}{space 3}0.588{col 60}{space 4}-.0167059{col 73}{space 3} .0294485
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2}-.3142827{col 32}{space 2} .3288515{col 43}{space 1}   -0.96{col 52}{space 3}0.339{col 60}{space 4}-.9588198{col 73}{space 3} .3302544
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2} .0414022{col 32}{space 2} .0315138{col 43}{space 1}    1.31{col 52}{space 3}0.189{col 60}{space 4}-.0203638{col 73}{space 3} .1031682
{txt}{space 18} {c |}
{space 2}birthstate_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2} 2.835834{col 32}{space 2}   2.2512{col 43}{space 1}    1.26{col 52}{space 3}0.208{col 60}{space 4}-1.576436{col 73}{space 3} 7.248104
{txt}{space 16}3  {c |}{col 20}{res}{space 2}-.8699586{col 32}{space 2} 1.046922{col 43}{space 1}   -0.83{col 52}{space 3}0.406{col 60}{space 4}-2.921889{col 73}{space 3} 1.181972
{txt}{space 16}4  {c |}{col 20}{res}{space 2} 3.873652{col 32}{space 2} 1.980629{col 43}{space 1}    1.96{col 52}{space 3}0.050{col 60}{space 4}-.0083088{col 73}{space 3} 7.755613
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-1.108315{col 32}{space 2} 1.937747{col 43}{space 1}   -0.57{col 52}{space 3}0.567{col 60}{space 4} -4.90623{col 73}{space 3} 2.689599
{txt}{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}13  {c |}{col 20}{res}{space 2}-.5128745{col 32}{space 2} .9582194{col 43}{space 1}   -0.54{col 52}{space 3}0.592{col 60}{space 4} -2.39095{col 73}{space 3} 1.365201
{txt}{space 15}14  {c |}{col 20}{res}{space 2}-.3846611{col 32}{space 2} 1.027166{col 43}{space 1}   -0.37{col 52}{space 3}0.708{col 60}{space 4} -2.39787{col 73}{space 3} 1.628548
{txt}{space 15}21  {c |}{col 20}{res}{space 2}-.3801038{col 32}{space 2}  1.00066{col 43}{space 1}   -0.38{col 52}{space 3}0.704{col 60}{space 4}-2.341362{col 73}{space 3} 1.581155
{txt}{space 15}22  {c |}{col 20}{res}{space 2} 1.114692{col 32}{space 2} 1.207536{col 43}{space 1}    0.92{col 52}{space 3}0.356{col 60}{space 4}-1.252034{col 73}{space 3} 3.481419
{txt}{space 15}23  {c |}{col 20}{res}{space 2} .2459786{col 32}{space 2} 1.028457{col 43}{space 1}    0.24{col 52}{space 3}0.811{col 60}{space 4}-1.769759{col 73}{space 3} 2.261716
{txt}{space 15}24  {c |}{col 20}{res}{space 2}-.6373019{col 32}{space 2} 1.239087{col 43}{space 1}   -0.51{col 52}{space 3}0.607{col 60}{space 4}-3.065867{col 73}{space 3} 1.791264
{txt}{space 15}25  {c |}{col 20}{res}{space 2} .4375311{col 32}{space 2} 1.347922{col 43}{space 1}    0.32{col 52}{space 3}0.745{col 60}{space 4}-2.204348{col 73}{space 3}  3.07941
{txt}{space 15}31  {c |}{col 20}{res}{space 2}-2.557872{col 32}{space 2} 1.487943{col 43}{space 1}   -1.72{col 52}{space 3}0.086{col 60}{space 4}-5.474186{col 73}{space 3} .3584422
{txt}{space 15}32  {c |}{col 20}{res}{space 2} 4.886783{col 32}{space 2} 1.979866{col 43}{space 1}    2.47{col 52}{space 3}0.014{col 60}{space 4} 1.006317{col 73}{space 3} 8.767249
{txt}{space 15}33  {c |}{col 20}{res}{space 2}-.3250909{col 32}{space 2} 1.167905{col 43}{space 1}   -0.28{col 52}{space 3}0.781{col 60}{space 4}-2.614142{col 73}{space 3}  1.96396
{txt}{space 15}34  {c |}{col 20}{res}{space 2} .1274751{col 32}{space 2} 1.237487{col 43}{space 1}    0.10{col 52}{space 3}0.918{col 60}{space 4}-2.297955{col 73}{space 3} 2.552905
{txt}{space 15}35  {c |}{col 20}{res}{space 2} .7866155{col 32}{space 2} 1.614159{col 43}{space 1}    0.49{col 52}{space 3}0.626{col 60}{space 4}-2.377077{col 73}{space 3} 3.950308
{txt}{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}37  {c |}{col 20}{res}{space 2} .3191576{col 32}{space 2} 1.623357{col 43}{space 1}    0.20{col 52}{space 3}0.844{col 60}{space 4}-2.862563{col 73}{space 3} 3.500878
{txt}{space 15}40  {c |}{col 20}{res}{space 2} 1.427819{col 32}{space 2} 1.276762{col 43}{space 1}    1.12{col 52}{space 3}0.263{col 60}{space 4}-1.074589{col 73}{space 3} 3.930227
{txt}{space 15}41  {c |}{col 20}{res}{space 2}-.2954091{col 32}{space 2} 1.322932{col 43}{space 1}   -0.22{col 52}{space 3}0.823{col 60}{space 4}-2.888308{col 73}{space 3}  2.29749
{txt}{space 15}42  {c |}{col 20}{res}{space 2} 1.301796{col 32}{space 2} 1.334329{col 43}{space 1}    0.98{col 52}{space 3}0.329{col 60}{space 4}-1.313442{col 73}{space 3} 3.917033
{txt}{space 15}43  {c |}{col 20}{res}{space 2} 3.408883{col 32}{space 2} 1.090666{col 43}{space 1}    3.13{col 52}{space 3}0.002{col 60}{space 4} 1.271217{col 73}{space 3} 5.546548
{txt}{space 15}44  {c |}{col 20}{res}{space 2}  1.46812{col 32}{space 2} 1.113656{col 43}{space 1}    1.32{col 52}{space 3}0.187{col 60}{space 4}-.7146058{col 73}{space 3} 3.650847
{txt}{space 15}45  {c |}{col 20}{res}{space 2}-2.019333{col 32}{space 2} 1.608314{col 43}{space 1}   -1.26{col 52}{space 3}0.209{col 60}{space 4} -5.17157{col 73}{space 3} 1.132905
{txt}{space 15}46  {c |}{col 20}{res}{space 2}-2.498982{col 32}{space 2} 2.269617{col 43}{space 1}   -1.10{col 52}{space 3}0.271{col 60}{space 4}-6.947349{col 73}{space 3} 1.949385
{txt}{space 15}47  {c |}{col 20}{res}{space 2} .6375379{col 32}{space 2} 1.135944{col 43}{space 1}    0.56{col 52}{space 3}0.575{col 60}{space 4}-1.588871{col 73}{space 3} 2.863947
{txt}{space 15}48  {c |}{col 20}{res}{space 2} .7352298{col 32}{space 2} 1.415091{col 43}{space 1}    0.52{col 52}{space 3}0.603{col 60}{space 4}-2.038297{col 73}{space 3} 3.508757
{txt}{space 15}49  {c |}{col 20}{res}{space 2} 2.690268{col 32}{space 2} 1.105787{col 43}{space 1}    2.43{col 52}{space 3}0.015{col 60}{space 4} .5229651{col 73}{space 3} 4.857571
{txt}{space 15}51  {c |}{col 20}{res}{space 2}-.7947633{col 32}{space 2} 1.431972{col 43}{space 1}   -0.56{col 52}{space 3}0.579{col 60}{space 4}-3.601376{col 73}{space 3} 2.011849
{txt}{space 15}52  {c |}{col 20}{res}{space 2} .4536324{col 32}{space 2}  1.18468{col 43}{space 1}    0.38{col 52}{space 3}0.702{col 60}{space 4}-1.868297{col 73}{space 3} 2.775562
{txt}{space 15}53  {c |}{col 20}{res}{space 2} 2.521312{col 32}{space 2} 1.248087{col 43}{space 1}    2.02{col 52}{space 3}0.043{col 60}{space 4} .0751071{col 73}{space 3} 4.967517
{txt}{space 15}54  {c |}{col 20}{res}{space 2} .0545013{col 32}{space 2}  1.23073{col 43}{space 1}    0.04{col 52}{space 3}0.965{col 60}{space 4}-2.357685{col 73}{space 3} 2.466687
{txt}{space 15}56  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}61  {c |}{col 20}{res}{space 2}  3.68697{col 32}{space 2} 1.267902{col 43}{space 1}    2.91{col 52}{space 3}0.004{col 60}{space 4} 1.201927{col 73}{space 3} 6.172013
{txt}{space 15}62  {c |}{col 20}{res}{space 2} 3.407319{col 32}{space 2}  1.47632{col 43}{space 1}    2.31{col 52}{space 3}0.021{col 60}{space 4} .5137841{col 73}{space 3} 6.300854
{txt}{space 15}63  {c |}{col 20}{res}{space 2} 2.443966{col 32}{space 2} 1.831725{col 43}{space 1}    1.33{col 52}{space 3}0.182{col 60}{space 4}-1.146148{col 73}{space 3} 6.034081
{txt}{space 15}64  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}65  {c |}{col 20}{res}{space 2} 4.710118{col 32}{space 2} 1.875911{col 43}{space 1}    2.51{col 52}{space 3}0.012{col 60}{space 4}   1.0334{col 73}{space 3} 8.386837
{txt}{space 15}66  {c |}{col 20}{res}{space 2} 2.101739{col 32}{space 2} 1.364328{col 43}{space 1}    1.54{col 52}{space 3}0.123{col 60}{space 4}-.5722952{col 73}{space 3} 4.775773
{txt}{space 15}67  {c |}{col 20}{res}{space 2} 4.450108{col 32}{space 2} 2.065673{col 43}{space 1}    2.15{col 52}{space 3}0.031{col 60}{space 4} .4014625{col 73}{space 3} 8.498753
{txt}{space 15}68  {c |}{col 20}{res}{space 2} 1.261865{col 32}{space 2} 1.832729{col 43}{space 1}    0.69{col 52}{space 3}0.491{col 60}{space 4}-2.330219{col 73}{space 3} 4.853948
{txt}{space 15}71  {c |}{col 20}{res}{space 2} 3.727398{col 32}{space 2} 1.055818{col 43}{space 1}    3.53{col 52}{space 3}0.000{col 60}{space 4} 1.658033{col 73}{space 3} 5.796762
{txt}{space 15}72  {c |}{col 20}{res}{space 2} .5625973{col 32}{space 2} 1.446145{col 43}{space 1}    0.39{col 52}{space 3}0.697{col 60}{space 4}-2.271796{col 73}{space 3}  3.39699
{txt}{space 15}73  {c |}{col 20}{res}{space 2} 1.610279{col 32}{space 2} 1.175439{col 43}{space 1}    1.37{col 52}{space 3}0.171{col 60}{space 4}-.6935384{col 73}{space 3} 3.914097
{txt}{space 15}82  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}98  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}99  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}100  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}101  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}102  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}103  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}104  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}105  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}106  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}107  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}108  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}109  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}110  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}111  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}112  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}113  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}114  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}115  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}116  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}117  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}118  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 3}Rep_state_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-.3701108{col 32}{space 2}  2.09305{col 43}{space 1}   -0.18{col 52}{space 3}0.860{col 60}{space 4}-4.472413{col 73}{space 3} 3.732191
{txt}{space 16}3  {c |}{col 20}{res}{space 2} 1.360075{col 32}{space 2} 1.104848{col 43}{space 1}    1.23{col 52}{space 3}0.218{col 60}{space 4} -.805388{col 73}{space 3} 3.525538
{txt}{space 16}4  {c |}{col 20}{res}{space 2}-3.587018{col 32}{space 2} 1.835497{col 43}{space 1}   -1.95{col 52}{space 3}0.051{col 60}{space 4}-7.184526{col 73}{space 3} .0104906
{txt}{space 16}5  {c |}{col 20}{res}{space 2} 1.240517{col 32}{space 2} 1.945457{col 43}{space 1}    0.64{col 52}{space 3}0.524{col 60}{space 4}-2.572507{col 73}{space 3} 5.053542
{txt}{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}12  {c |}{col 20}{res}{space 2}  .036328{col 32}{space 2} 1.023301{col 43}{space 1}    0.04{col 52}{space 3}0.972{col 60}{space 4}-1.969305{col 73}{space 3} 2.041961
{txt}{space 15}13  {c |}{col 20}{res}{space 2} 1.979769{col 32}{space 2} .9185416{col 43}{space 1}    2.16{col 52}{space 3}0.031{col 60}{space 4} .1794606{col 73}{space 3} 3.780078
{txt}{space 15}14  {c |}{col 20}{res}{space 2}  2.01763{col 32}{space 2} 1.017614{col 43}{space 1}    1.98{col 52}{space 3}0.047{col 60}{space 4} .0231444{col 73}{space 3} 4.012117
{txt}{space 15}21  {c |}{col 20}{res}{space 2} 1.387015{col 32}{space 2} .9577211{col 43}{space 1}    1.45{col 52}{space 3}0.148{col 60}{space 4}-.4900836{col 73}{space 3} 3.264114
{txt}{space 15}22  {c |}{col 20}{res}{space 2} .1254053{col 32}{space 2} 1.083143{col 43}{space 1}    0.12{col 52}{space 3}0.908{col 60}{space 4}-1.997516{col 73}{space 3} 2.248326
{txt}{space 15}23  {c |}{col 20}{res}{space 2} 1.180633{col 32}{space 2} 1.007989{col 43}{space 1}    1.17{col 52}{space 3}0.241{col 60}{space 4}-.7949889{col 73}{space 3} 3.156254
{txt}{space 15}24  {c |}{col 20}{res}{space 2} 3.156367{col 32}{space 2} 1.317907{col 43}{space 1}    2.39{col 52}{space 3}0.017{col 60}{space 4} .5733158{col 73}{space 3} 5.739418
{txt}{space 15}25  {c |}{col 20}{res}{space 2} 1.068608{col 32}{space 2} 1.330809{col 43}{space 1}    0.80{col 52}{space 3}0.422{col 60}{space 4} -1.53973{col 73}{space 3} 3.676946
{txt}{space 15}31  {c |}{col 20}{res}{space 2} 4.641641{col 32}{space 2}  1.78493{col 43}{space 1}    2.60{col 52}{space 3}0.009{col 60}{space 4} 1.143242{col 73}{space 3} 8.140039
{txt}{space 15}32  {c |}{col 20}{res}{space 2}-2.569326{col 32}{space 2} 1.793455{col 43}{space 1}   -1.43{col 52}{space 3}0.152{col 60}{space 4}-6.084434{col 73}{space 3} .9457811
{txt}{space 15}33  {c |}{col 20}{res}{space 2} -.309879{col 32}{space 2} 1.169706{col 43}{space 1}   -0.26{col 52}{space 3}0.791{col 60}{space 4} -2.60246{col 73}{space 3} 1.982702
{txt}{space 15}34  {c |}{col 20}{res}{space 2} 1.106829{col 32}{space 2} 1.210552{col 43}{space 1}    0.91{col 52}{space 3}0.361{col 60}{space 4}-1.265809{col 73}{space 3} 3.479466
{txt}{space 15}35  {c |}{col 20}{res}{space 2} .9625504{col 32}{space 2}  1.55575{col 43}{space 1}    0.62{col 52}{space 3}0.536{col 60}{space 4}-2.086663{col 73}{space 3} 4.011764
{txt}{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}37  {c |}{col 20}{res}{space 2} 1.142485{col 32}{space 2} 1.703224{col 43}{space 1}    0.67{col 52}{space 3}0.502{col 60}{space 4}-2.195772{col 73}{space 3} 4.480742
{txt}{space 15}40  {c |}{col 20}{res}{space 2}-1.758987{col 32}{space 2} 1.098183{col 43}{space 1}   -1.60{col 52}{space 3}0.109{col 60}{space 4}-3.911387{col 73}{space 3}  .393412
{txt}{space 15}41  {c |}{col 20}{res}{space 2} 2.080054{col 32}{space 2} 1.380707{col 43}{space 1}    1.51{col 52}{space 3}0.132{col 60}{space 4} -.626083{col 73}{space 3} 4.786191
{txt}{space 15}42  {c |}{col 20}{res}{space 2}-.4073141{col 32}{space 2} 1.327959{col 43}{space 1}   -0.31{col 52}{space 3}0.759{col 60}{space 4}-3.010067{col 73}{space 3} 2.195439
{txt}{space 15}43  {c |}{col 20}{res}{space 2}-2.029909{col 32}{space 2} .9599215{col 43}{space 1}   -2.11{col 52}{space 3}0.034{col 60}{space 4} -3.91132{col 73}{space 3} -.148497
{txt}{space 15}44  {c |}{col 20}{res}{space 2}-.2489008{col 32}{space 2} 1.058803{col 43}{space 1}   -0.24{col 52}{space 3}0.814{col 60}{space 4}-2.324116{col 73}{space 3} 1.826315
{txt}{space 15}45  {c |}{col 20}{res}{space 2} 4.437132{col 32}{space 2} 1.712963{col 43}{space 1}    2.59{col 52}{space 3}0.010{col 60}{space 4} 1.079787{col 73}{space 3} 7.794477
{txt}{space 15}46  {c |}{col 20}{res}{space 2} 4.725705{col 32}{space 2} 2.422659{col 43}{space 1}    1.95{col 52}{space 3}0.051{col 60}{space 4}-.0226205{col 73}{space 3}  9.47403
{txt}{space 15}47  {c |}{col 20}{res}{space 2} .2339885{col 32}{space 2} 1.079759{col 43}{space 1}    0.22{col 52}{space 3}0.828{col 60}{space 4}  -1.8823{col 73}{space 3} 2.350277
{txt}{space 15}48  {c |}{col 20}{res}{space 2}  .413279{col 32}{space 2} 1.398461{col 43}{space 1}    0.30{col 52}{space 3}0.768{col 60}{space 4}-2.327654{col 73}{space 3} 3.154212
{txt}{space 15}49  {c |}{col 20}{res}{space 2} -.764345{col 32}{space 2} 1.044502{col 43}{space 1}   -0.73{col 52}{space 3}0.464{col 60}{space 4}-2.811531{col 73}{space 3}  1.28284
{txt}{space 15}51  {c |}{col 20}{res}{space 2} 2.295182{col 32}{space 2} 1.518993{col 43}{space 1}    1.51{col 52}{space 3}0.131{col 60}{space 4}-.6819888{col 73}{space 3} 5.272353
{txt}{space 15}52  {c |}{col 20}{res}{space 2}-.6367585{col 32}{space 2} 1.074996{col 43}{space 1}   -0.59{col 52}{space 3}0.554{col 60}{space 4}-2.743712{col 73}{space 3} 1.470195
{txt}{space 15}53  {c |}{col 20}{res}{space 2}-2.097068{col 32}{space 2} 1.205435{col 43}{space 1}   -1.74{col 52}{space 3}0.082{col 60}{space 4}-4.459677{col 73}{space 3} .2655405
{txt}{space 15}54  {c |}{col 20}{res}{space 2} 1.131144{col 32}{space 2} 1.187412{col 43}{space 1}    0.95{col 52}{space 3}0.341{col 60}{space 4} -1.19614{col 73}{space 3} 3.458428
{txt}{space 15}56  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}61  {c |}{col 20}{res}{space 2}-2.787459{col 32}{space 2} 1.177393{col 43}{space 1}   -2.37{col 52}{space 3}0.018{col 60}{space 4}-5.095108{col 73}{space 3}-.4798101
{txt}{space 15}62  {c |}{col 20}{res}{space 2}-2.682514{col 32}{space 2} 1.328878{col 43}{space 1}   -2.02{col 52}{space 3}0.044{col 60}{space 4}-5.287067{col 73}{space 3}-.0779611
{txt}{space 15}63  {c |}{col 20}{res}{space 2}-1.240467{col 32}{space 2} 1.731617{col 43}{space 1}   -0.72{col 52}{space 3}0.474{col 60}{space 4}-4.634374{col 73}{space 3} 2.153439
{txt}{space 15}64  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}65  {c |}{col 20}{res}{space 2}-3.177758{col 32}{space 2} 1.655732{col 43}{space 1}   -1.92{col 52}{space 3}0.055{col 60}{space 4}-6.422933{col 73}{space 3} .0674175
{txt}{space 15}66  {c |}{col 20}{res}{space 2}-3.740649{col 32}{space 2} 1.326152{col 43}{space 1}   -2.82{col 52}{space 3}0.005{col 60}{space 4}-6.339859{col 73}{space 3}-1.141439
{txt}{space 15}67  {c |}{col 20}{res}{space 2} -2.33938{col 32}{space 2} 2.003891{col 43}{space 1}   -1.17{col 52}{space 3}0.243{col 60}{space 4}-6.266934{col 73}{space 3} 1.588173
{txt}{space 15}68  {c |}{col 20}{res}{space 2}-2.130158{col 32}{space 2} 1.914584{col 43}{space 1}   -1.11{col 52}{space 3}0.266{col 60}{space 4}-5.882674{col 73}{space 3} 1.622358
{txt}{space 15}71  {c |}{col 20}{res}{space 2}-2.176879{col 32}{space 2} .9612362{col 43}{space 1}   -2.26{col 52}{space 3}0.024{col 60}{space 4}-4.060868{col 73}{space 3}-.2928911
{txt}{space 15}72  {c |}{col 20}{res}{space 2}-.6108496{col 32}{space 2} 1.312035{col 43}{space 1}   -0.47{col 52}{space 3}0.642{col 60}{space 4}-3.182392{col 73}{space 3} 1.960692
{txt}{space 15}73  {c |}{col 20}{res}{space 2}-.8671915{col 32}{space 2} 1.154185{col 43}{space 1}   -0.75{col 52}{space 3}0.452{col 60}{space 4}-3.129352{col 73}{space 3} 1.394969
{txt}{space 15}81  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}82  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} .6424531{col 32}{space 2} 1.214823{col 43}{space 1}    0.53{col 52}{space 3}0.597{col 60}{space 4}-1.738556{col 73}{space 3} 3.023463
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_instate]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_instate]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}   10.98
{txt}{col 10}Prob > chi2 =  {res}  0.1396
{txt}
{com}. 
. *Democrats - Column 3
. logit born_instate AgeInteger Female Black Hispanic dpres i.birthstate_icpsr i.Rep_state_icpsr if congress<116 & party_code==100

{txt}note: 2.birthstate_icpsr != 0 predicts success perfectly
      2.birthstate_icpsr dropped and 3 obs not used

note: 4.birthstate_icpsr != 0 predicts success perfectly
      4.birthstate_icpsr dropped and 1 obs not used

note: 5.birthstate_icpsr != 0 predicts success perfectly
      5.birthstate_icpsr dropped and 2 obs not used

note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 1 obs not used

note: 32.birthstate_icpsr != 0 predicts success perfectly
      32.birthstate_icpsr dropped and 1 obs not used

note: 40.birthstate_icpsr != 0 predicts success perfectly
      40.birthstate_icpsr dropped and 2 obs not used

note: 46.birthstate_icpsr != 0 predicts success perfectly
      46.birthstate_icpsr dropped and 3 obs not used

note: 67.birthstate_icpsr != 0 predicts success perfectly
      67.birthstate_icpsr dropped and 1 obs not used

note: 82.birthstate_icpsr != 0 predicts success perfectly
      82.birthstate_icpsr dropped and 4 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 7 obs not used

note: 99.birthstate_icpsr != 0 predicts failure perfectly
      99.birthstate_icpsr dropped and 1 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 1 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 1 obs not used

note: 102.birthstate_icpsr != 0 predicts failure perfectly
      102.birthstate_icpsr dropped and 1 obs not used

note: 103.birthstate_icpsr != 0 predicts failure perfectly
      103.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 1 obs not used

note: 106.birthstate_icpsr != 0 predicts failure perfectly
      106.birthstate_icpsr dropped and 1 obs not used

note: 107.birthstate_icpsr != 0 predicts failure perfectly
      107.birthstate_icpsr dropped and 1 obs not used

note: 108.birthstate_icpsr != 0 predicts failure perfectly
      108.birthstate_icpsr dropped and 2 obs not used

note: 109.birthstate_icpsr != 0 predicts failure perfectly
      109.birthstate_icpsr dropped and 1 obs not used

note: 110.birthstate_icpsr != 0 predicts failure perfectly
      110.birthstate_icpsr dropped and 2 obs not used

note: 111.birthstate_icpsr != 0 predicts failure perfectly
      111.birthstate_icpsr dropped and 4 obs not used

note: 113.birthstate_icpsr != 0 predicts failure perfectly
      113.birthstate_icpsr dropped and 1 obs not used

note: 114.birthstate_icpsr != 0 predicts failure perfectly
      114.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 2 obs not used

note: 116.birthstate_icpsr != 0 predicts failure perfectly
      116.birthstate_icpsr dropped and 2 obs not used

note: 117.birthstate_icpsr != 0 predicts failure perfectly
      117.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 1 obs not used

note: 2.Rep_state_icpsr != 0 predicts failure perfectly
      2.Rep_state_icpsr dropped and 1 obs not used

note: 33.birthstate_icpsr != 0 predicts success perfectly
      33.birthstate_icpsr dropped and 4 obs not used

note: 4.Rep_state_icpsr != 0 predicts failure perfectly
      4.Rep_state_icpsr dropped and 2 obs not used

note: 5.Rep_state_icpsr != 0 predicts failure perfectly
      5.Rep_state_icpsr dropped and 1 obs not used

note: 6.Rep_state_icpsr != 0 predicts failure perfectly
      6.Rep_state_icpsr dropped and 1 obs not used

note: 11.Rep_state_icpsr != 0 predicts failure perfectly
      11.Rep_state_icpsr dropped and 1 obs not used

note: 24.Rep_state_icpsr != 0 predicts success perfectly
      24.Rep_state_icpsr dropped and 17 obs not used

note: 24.birthstate_icpsr != 0 predicts failure perfectly
      24.birthstate_icpsr dropped and 3 obs not used

note: 32.Rep_state_icpsr != 0 predicts failure perfectly
      32.Rep_state_icpsr dropped and 1 obs not used

note: 33.Rep_state_icpsr != 0 predicts failure perfectly
      33.Rep_state_icpsr dropped and 4 obs not used

note: 35.birthstate_icpsr != 0 predicts success perfectly
      35.birthstate_icpsr dropped and 1 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 1 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 1 obs not used

note: 37.Rep_state_icpsr != 0 predicts success perfectly
      37.Rep_state_icpsr dropped and 1 obs not used

note: 37.birthstate_icpsr != 0 predicts failure perfectly
      37.birthstate_icpsr dropped and 1 obs not used

note: 40.Rep_state_icpsr != 0 predicts failure perfectly
      40.Rep_state_icpsr dropped and 4 obs not used

note: 45.Rep_state_icpsr != 0 predicts success perfectly
      45.Rep_state_icpsr dropped and 6 obs not used

note: 45.birthstate_icpsr != 0 predicts failure perfectly
      45.birthstate_icpsr dropped and 3 obs not used

note: 41.Rep_state_icpsr != 0 predicts success perfectly
      41.Rep_state_icpsr dropped and 5 obs not used

note: 41.birthstate_icpsr != 0 predicts failure perfectly
      41.birthstate_icpsr dropped and 4 obs not used

note: 51.Rep_state_icpsr != 0 predicts success perfectly
      51.Rep_state_icpsr dropped and 3 obs not used

note: 51.birthstate_icpsr != 0 predicts failure perfectly
      51.birthstate_icpsr dropped and 2 obs not used

note: 54.Rep_state_icpsr != 0 predicts success perfectly
      54.Rep_state_icpsr dropped and 7 obs not used

note: 54.birthstate_icpsr != 0 predicts failure perfectly
      54.birthstate_icpsr dropped and 2 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 2 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 2 obs not used

note: 63.Rep_state_icpsr != 0 predicts failure perfectly
      63.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 1 obs not used

note: 35.Rep_state_icpsr omitted because of collinearity
note: 46.Rep_state_icpsr omitted because of collinearity
note: 67.Rep_state_icpsr omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-193.38285}  
Iteration 1:{space 3}log likelihood = {res:-115.19996}  
Iteration 2:{space 3}log likelihood = {res:-111.62051}  
Iteration 3:{space 3}log likelihood = {res:-111.42533}  
Iteration 4:{space 3}log likelihood = {res:-111.42492}  
Iteration 5:{space 3}log likelihood = {res:-111.42492}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       312
{txt}{col 49}LR chi2({res}55{txt}){col 67}= {res}    163.92
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-111.42492{txt}{col 49}Pseudo R2{col 67}= {res}    0.4238

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    born_instate{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}AgeInteger {c |}{col 18}{res}{space 2}-.0508855{col 30}{space 2} .0220809{col 41}{space 1}   -2.30{col 50}{space 3}0.021{col 58}{space 4}-.0941634{col 71}{space 3}-.0076076
{txt}{space 10}Female {c |}{col 18}{res}{space 2}-.5369873{col 30}{space 2}   .48827{col 41}{space 1}   -1.10{col 50}{space 3}0.271{col 58}{space 4}-1.493979{col 71}{space 3} .4200044
{txt}{space 11}Black {c |}{col 18}{res}{space 2} .4817187{col 30}{space 2} .7746182{col 41}{space 1}    0.62{col 50}{space 3}0.534{col 58}{space 4}-1.036505{col 71}{space 3} 1.999942
{txt}{space 8}Hispanic {c |}{col 18}{res}{space 2} .7081386{col 30}{space 2} .7750479{col 41}{space 1}    0.91{col 50}{space 3}0.361{col 58}{space 4}-.8109274{col 71}{space 3} 2.227205
{txt}{space 11}dpres {c |}{col 18}{res}{space 2} .0061225{col 30}{space 2} .0223073{col 41}{space 1}    0.27{col 50}{space 3}0.784{col 58}{space 4} -.037599{col 71}{space 3}  .049844
{txt}{space 16} {c |}
birthstate_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}3  {c |}{col 18}{res}{space 2}-.1434586{col 30}{space 2} 1.446595{col 41}{space 1}   -0.10{col 50}{space 3}0.921{col 58}{space 4}-2.978733{col 71}{space 3} 2.691816
{txt}{space 14}4  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}5  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2}-2.693943{col 30}{space 2} 1.798974{col 41}{space 1}   -1.50{col 50}{space 3}0.134{col 58}{space 4}-6.219867{col 71}{space 3} .8319805
{txt}{space 13}13  {c |}{col 18}{res}{space 2}-5.548781{col 30}{space 2}  1.88344{col 41}{space 1}   -2.95{col 50}{space 3}0.003{col 58}{space 4}-9.240255{col 71}{space 3}-1.857307
{txt}{space 13}14  {c |}{col 18}{res}{space 2}-3.311366{col 30}{space 2} 1.879026{col 41}{space 1}   -1.76{col 50}{space 3}0.078{col 58}{space 4} -6.99419{col 71}{space 3} .3714575
{txt}{space 13}21  {c |}{col 18}{res}{space 2}-1.061476{col 30}{space 2} 1.606927{col 41}{space 1}   -0.66{col 50}{space 3}0.509{col 58}{space 4}-4.210996{col 71}{space 3} 2.088044
{txt}{space 13}22  {c |}{col 18}{res}{space 2}-2.924059{col 30}{space 2} 2.271365{col 41}{space 1}   -1.29{col 50}{space 3}0.198{col 58}{space 4}-7.375853{col 71}{space 3} 1.527734
{txt}{space 13}23  {c |}{col 18}{res}{space 2} 1.978106{col 30}{space 2} 2.138675{col 41}{space 1}    0.92{col 50}{space 3}0.355{col 58}{space 4} -2.21362{col 71}{space 3} 6.169833
{txt}{space 13}24  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}25  {c |}{col 18}{res}{space 2}-2.723652{col 30}{space 2} 2.126558{col 41}{space 1}   -1.28{col 50}{space 3}0.200{col 58}{space 4}-6.891629{col 71}{space 3} 1.444325
{txt}{space 13}31  {c |}{col 18}{res}{space 2}-4.314726{col 30}{space 2} 2.695592{col 41}{space 1}   -1.60{col 50}{space 3}0.109{col 58}{space 4} -9.59799{col 71}{space 3} .9685376
{txt}{space 13}32  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}33  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}34  {c |}{col 18}{res}{space 2}-2.330107{col 30}{space 2} 2.614801{col 41}{space 1}   -0.89{col 50}{space 3}0.373{col 58}{space 4}-7.455023{col 71}{space 3} 2.794809
{txt}{space 13}35  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}37  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}40  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}41  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}42  {c |}{col 18}{res}{space 2}-1.897301{col 30}{space 2}  2.15193{col 41}{space 1}   -0.88{col 50}{space 3}0.378{col 58}{space 4}-6.115007{col 71}{space 3} 2.320405
{txt}{space 13}43  {c |}{col 18}{res}{space 2} 1.278884{col 30}{space 2}  1.93091{col 41}{space 1}    0.66{col 50}{space 3}0.508{col 58}{space 4}-2.505629{col 71}{space 3} 5.063398
{txt}{space 13}44  {c |}{col 18}{res}{space 2}-5.763856{col 30}{space 2} 2.486117{col 41}{space 1}   -2.32{col 50}{space 3}0.020{col 58}{space 4}-10.63656{col 71}{space 3}-.8911567
{txt}{space 13}45  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}46  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}47  {c |}{col 18}{res}{space 2}-8.496275{col 30}{space 2} 2.434366{col 41}{space 1}   -3.49{col 50}{space 3}0.000{col 58}{space 4}-13.26754{col 71}{space 3}-3.725005
{txt}{space 13}48  {c |}{col 18}{res}{space 2}-8.443784{col 30}{space 2} 2.523344{col 41}{space 1}   -3.35{col 50}{space 3}0.001{col 58}{space 4}-13.38945{col 71}{space 3}-3.498121
{txt}{space 13}49  {c |}{col 18}{res}{space 2} 1.803692{col 30}{space 2} 1.983249{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-2.083405{col 71}{space 3} 5.690788
{txt}{space 13}51  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}52  {c |}{col 18}{res}{space 2}-1.228454{col 30}{space 2} 2.361279{col 41}{space 1}   -0.52{col 50}{space 3}0.603{col 58}{space 4}-5.856475{col 71}{space 3} 3.399567
{txt}{space 13}53  {c |}{col 18}{res}{space 2}-3.593194{col 30}{space 2} 2.578844{col 41}{space 1}   -1.39{col 50}{space 3}0.164{col 58}{space 4}-8.647636{col 71}{space 3} 1.461247
{txt}{space 13}54  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}56  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}61  {c |}{col 18}{res}{space 2} -1.66747{col 30}{space 2} 2.020675{col 41}{space 1}   -0.83{col 50}{space 3}0.409{col 58}{space 4} -5.62792{col 71}{space 3} 2.292979
{txt}{space 13}62  {c |}{col 18}{res}{space 2}-1.722531{col 30}{space 2} 1.997507{col 41}{space 1}   -0.86{col 50}{space 3}0.389{col 58}{space 4}-5.637572{col 71}{space 3}  2.19251
{txt}{space 13}65  {c |}{col 18}{res}{space 2}-2.049272{col 30}{space 2} 2.564013{col 41}{space 1}   -0.80{col 50}{space 3}0.424{col 58}{space 4}-7.074645{col 71}{space 3} 2.976101
{txt}{space 13}66  {c |}{col 18}{res}{space 2}-.8927681{col 30}{space 2} 2.181854{col 41}{space 1}   -0.41{col 50}{space 3}0.682{col 58}{space 4}-5.169124{col 71}{space 3} 3.383588
{txt}{space 13}67  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}71  {c |}{col 18}{res}{space 2} 4.510304{col 30}{space 2} 1.816562{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4} .9499086{col 71}{space 3}   8.0707
{txt}{space 13}72  {c |}{col 18}{res}{space 2}-.3803224{col 30}{space 2} 2.598684{col 41}{space 1}   -0.15{col 50}{space 3}0.884{col 58}{space 4} -5.47365{col 71}{space 3} 4.713005
{txt}{space 13}73  {c |}{col 18}{res}{space 2} .8315671{col 30}{space 2} 2.083841{col 41}{space 1}    0.40{col 50}{space 3}0.690{col 58}{space 4}-3.252687{col 71}{space 3} 4.915821
{txt}{space 13}82  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}98  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}99  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}100  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}101  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}102  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}103  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}105  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}106  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}107  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}108  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}109  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}110  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}111  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}113  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}114  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}115  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}116  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}117  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}118  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 1}Rep_state_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}3  {c |}{col 18}{res}{space 2} .7067292{col 30}{space 2}  1.44756{col 41}{space 1}    0.49{col 50}{space 3}0.625{col 58}{space 4}-2.130436{col 71}{space 3} 3.543894
{txt}{space 14}4  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}5  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}6  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2} 3.660172{col 30}{space 2} 1.856094{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0222951{col 71}{space 3} 7.298049
{txt}{space 13}13  {c |}{col 18}{res}{space 2} 6.860455{col 30}{space 2}  1.91073{col 41}{space 1}    3.59{col 50}{space 3}0.000{col 58}{space 4} 3.115494{col 71}{space 3} 10.60542
{txt}{space 13}14  {c |}{col 18}{res}{space 2} 4.677686{col 30}{space 2} 1.858496{col 41}{space 1}    2.52{col 50}{space 3}0.012{col 58}{space 4} 1.035101{col 71}{space 3} 8.320271
{txt}{space 13}21  {c |}{col 18}{res}{space 2} 1.353514{col 30}{space 2} 1.540929{col 41}{space 1}    0.88{col 50}{space 3}0.380{col 58}{space 4} -1.66665{col 71}{space 3} 4.373679
{txt}{space 13}22  {c |}{col 18}{res}{space 2} 4.146395{col 30}{space 2} 2.286974{col 41}{space 1}    1.81{col 50}{space 3}0.070{col 58}{space 4}-.3359925{col 71}{space 3} 8.628782
{txt}{space 13}23  {c |}{col 18}{res}{space 2} .6644785{col 30}{space 2} 2.098667{col 41}{space 1}    0.32{col 50}{space 3}0.752{col 58}{space 4}-3.448834{col 71}{space 3} 4.777791
{txt}{space 13}24  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}25  {c |}{col 18}{res}{space 2} 3.957642{col 30}{space 2} 2.285235{col 41}{space 1}    1.73{col 50}{space 3}0.083{col 58}{space 4}-.5213356{col 71}{space 3}  8.43662
{txt}{space 13}31  {c |}{col 18}{res}{space 2} 3.723997{col 30}{space 2} 2.723078{col 41}{space 1}    1.37{col 50}{space 3}0.171{col 58}{space 4}-1.613138{col 71}{space 3} 9.061131
{txt}{space 13}32  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}33  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}34  {c |}{col 18}{res}{space 2} 1.596444{col 30}{space 2} 2.501405{col 41}{space 1}    0.64{col 50}{space 3}0.523{col 58}{space 4}-3.306219{col 71}{space 3} 6.499107
{txt}{space 13}35  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}37  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}40  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}41  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}42  {c |}{col 18}{res}{space 2} 1.190787{col 30}{space 2} 2.382059{col 41}{space 1}    0.50{col 50}{space 3}0.617{col 58}{space 4}-3.477962{col 71}{space 3} 5.859537
{txt}{space 13}43  {c |}{col 18}{res}{space 2} .0870404{col 30}{space 2} 1.768986{col 41}{space 1}    0.05{col 50}{space 3}0.961{col 58}{space 4}-3.380109{col 71}{space 3}  3.55419
{txt}{space 13}44  {c |}{col 18}{res}{space 2} 4.525955{col 30}{space 2} 2.214839{col 41}{space 1}    2.04{col 50}{space 3}0.041{col 58}{space 4} .1849506{col 71}{space 3} 8.866958
{txt}{space 13}45  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}46  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}47  {c |}{col 18}{res}{space 2}  9.66835{col 30}{space 2} 2.645967{col 41}{space 1}    3.65{col 50}{space 3}0.000{col 58}{space 4} 4.482349{col 71}{space 3} 14.85435
{txt}{space 13}48  {c |}{col 18}{res}{space 2}  7.69505{col 30}{space 2} 2.702283{col 41}{space 1}    2.85{col 50}{space 3}0.004{col 58}{space 4} 2.398671{col 71}{space 3} 12.99143
{txt}{space 13}49  {c |}{col 18}{res}{space 2}-.5699469{col 30}{space 2} 1.964996{col 41}{space 1}   -0.29{col 50}{space 3}0.772{col 58}{space 4}-4.421268{col 71}{space 3} 3.281375
{txt}{space 13}51  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}52  {c |}{col 18}{res}{space 2}  1.47926{col 30}{space 2} 2.094114{col 41}{space 1}    0.71{col 50}{space 3}0.480{col 58}{space 4}-2.625129{col 71}{space 3} 5.583648
{txt}{space 13}53  {c |}{col 18}{res}{space 2} .7751542{col 30}{space 2}  2.57039{col 41}{space 1}    0.30{col 50}{space 3}0.763{col 58}{space 4}-4.262718{col 71}{space 3} 5.813026
{txt}{space 13}54  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}56  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}61  {c |}{col 18}{res}{space 2} 1.840312{col 30}{space 2} 1.990441{col 41}{space 1}    0.92{col 50}{space 3}0.355{col 58}{space 4}-2.060881{col 71}{space 3} 5.741505
{txt}{space 13}62  {c |}{col 18}{res}{space 2} 1.189677{col 30}{space 2} 1.946769{col 41}{space 1}    0.61{col 50}{space 3}0.541{col 58}{space 4}-2.625919{col 71}{space 3} 5.005274
{txt}{space 13}63  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}65  {c |}{col 18}{res}{space 2} .5051732{col 30}{space 2} 2.257392{col 41}{space 1}    0.22{col 50}{space 3}0.823{col 58}{space 4}-3.919234{col 71}{space 3} 4.929581
{txt}{space 13}66  {c |}{col 18}{res}{space 2}-.1607259{col 30}{space 2} 2.089828{col 41}{space 1}   -0.08{col 50}{space 3}0.939{col 58}{space 4}-4.256714{col 71}{space 3} 3.935262
{txt}{space 13}67  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}71  {c |}{col 18}{res}{space 2}-2.732537{col 30}{space 2} 1.611816{col 41}{space 1}   -1.70{col 50}{space 3}0.090{col 58}{space 4} -5.89164{col 71}{space 3} .4265649
{txt}{space 13}72  {c |}{col 18}{res}{space 2}-2.216221{col 30}{space 2} 1.829282{col 41}{space 1}   -1.21{col 50}{space 3}0.226{col 58}{space 4}-5.801548{col 71}{space 3} 1.369107
{txt}{space 13}73  {c |}{col 18}{res}{space 2}-.2223402{col 30}{space 2} 1.980367{col 41}{space 1}   -0.11{col 50}{space 3}0.911{col 58}{space 4}-4.103789{col 71}{space 3} 3.659108
{txt}{space 13}82  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}  3.21457{col 30}{space 2} 2.189095{col 41}{space 1}    1.47{col 50}{space 3}0.142{col 58}{space 4}-1.075978{col 71}{space 3} 7.505118
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    7.96
{txt}{col 10}Prob > chi2 =  {res}  0.1583
{txt}
{com}. 
. *Democrats - Column 4
. logit born_instate AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.birthstate_icpsr i.Rep_state_icpsr if congress<116 & party_code==100

{txt}note: 2.birthstate_icpsr != 0 predicts success perfectly
      2.birthstate_icpsr dropped and 3 obs not used

note: 4.birthstate_icpsr != 0 predicts success perfectly
      4.birthstate_icpsr dropped and 1 obs not used

note: 5.birthstate_icpsr != 0 predicts success perfectly
      5.birthstate_icpsr dropped and 2 obs not used

note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 1 obs not used

note: 32.birthstate_icpsr != 0 predicts success perfectly
      32.birthstate_icpsr dropped and 1 obs not used

note: 40.birthstate_icpsr != 0 predicts success perfectly
      40.birthstate_icpsr dropped and 2 obs not used

note: 46.birthstate_icpsr != 0 predicts success perfectly
      46.birthstate_icpsr dropped and 3 obs not used

note: 67.birthstate_icpsr != 0 predicts success perfectly
      67.birthstate_icpsr dropped and 1 obs not used

note: 82.birthstate_icpsr != 0 predicts success perfectly
      82.birthstate_icpsr dropped and 4 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 7 obs not used

note: 99.birthstate_icpsr != 0 predicts failure perfectly
      99.birthstate_icpsr dropped and 1 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 1 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 1 obs not used

note: 102.birthstate_icpsr != 0 predicts failure perfectly
      102.birthstate_icpsr dropped and 1 obs not used

note: 103.birthstate_icpsr != 0 predicts failure perfectly
      103.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 1 obs not used

note: 106.birthstate_icpsr != 0 predicts failure perfectly
      106.birthstate_icpsr dropped and 1 obs not used

note: 107.birthstate_icpsr != 0 predicts failure perfectly
      107.birthstate_icpsr dropped and 1 obs not used

note: 108.birthstate_icpsr != 0 predicts failure perfectly
      108.birthstate_icpsr dropped and 2 obs not used

note: 109.birthstate_icpsr != 0 predicts failure perfectly
      109.birthstate_icpsr dropped and 1 obs not used

note: 110.birthstate_icpsr != 0 predicts failure perfectly
      110.birthstate_icpsr dropped and 2 obs not used

note: 111.birthstate_icpsr != 0 predicts failure perfectly
      111.birthstate_icpsr dropped and 4 obs not used

note: 113.birthstate_icpsr != 0 predicts failure perfectly
      113.birthstate_icpsr dropped and 1 obs not used

note: 114.birthstate_icpsr != 0 predicts failure perfectly
      114.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 2 obs not used

note: 116.birthstate_icpsr != 0 predicts failure perfectly
      116.birthstate_icpsr dropped and 2 obs not used

note: 117.birthstate_icpsr != 0 predicts failure perfectly
      117.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 1 obs not used

note: 2.Rep_state_icpsr != 0 predicts failure perfectly
      2.Rep_state_icpsr dropped and 1 obs not used

note: 33.birthstate_icpsr != 0 predicts success perfectly
      33.birthstate_icpsr dropped and 4 obs not used

note: 4.Rep_state_icpsr != 0 predicts failure perfectly
      4.Rep_state_icpsr dropped and 2 obs not used

note: 5.Rep_state_icpsr != 0 predicts failure perfectly
      5.Rep_state_icpsr dropped and 1 obs not used

note: 6.Rep_state_icpsr != 0 predicts failure perfectly
      6.Rep_state_icpsr dropped and 1 obs not used

note: 11.Rep_state_icpsr != 0 predicts failure perfectly
      11.Rep_state_icpsr dropped and 1 obs not used

note: 24.Rep_state_icpsr != 0 predicts success perfectly
      24.Rep_state_icpsr dropped and 17 obs not used

note: 24.birthstate_icpsr != 0 predicts failure perfectly
      24.birthstate_icpsr dropped and 3 obs not used

note: 32.Rep_state_icpsr != 0 predicts failure perfectly
      32.Rep_state_icpsr dropped and 1 obs not used

note: 33.Rep_state_icpsr != 0 predicts failure perfectly
      33.Rep_state_icpsr dropped and 4 obs not used

note: 35.birthstate_icpsr != 0 predicts success perfectly
      35.birthstate_icpsr dropped and 1 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 1 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 1 obs not used

note: 37.Rep_state_icpsr != 0 predicts success perfectly
      37.Rep_state_icpsr dropped and 1 obs not used

note: 37.birthstate_icpsr != 0 predicts failure perfectly
      37.birthstate_icpsr dropped and 1 obs not used

note: 40.Rep_state_icpsr != 0 predicts failure perfectly
      40.Rep_state_icpsr dropped and 4 obs not used

note: 45.Rep_state_icpsr != 0 predicts success perfectly
      45.Rep_state_icpsr dropped and 6 obs not used

note: 45.birthstate_icpsr != 0 predicts failure perfectly
      45.birthstate_icpsr dropped and 3 obs not used

note: 41.Rep_state_icpsr != 0 predicts success perfectly
      41.Rep_state_icpsr dropped and 5 obs not used

note: 41.birthstate_icpsr != 0 predicts failure perfectly
      41.birthstate_icpsr dropped and 4 obs not used

note: 51.Rep_state_icpsr != 0 predicts success perfectly
      51.Rep_state_icpsr dropped and 3 obs not used

note: 51.birthstate_icpsr != 0 predicts failure perfectly
      51.birthstate_icpsr dropped and 2 obs not used

note: 54.Rep_state_icpsr != 0 predicts success perfectly
      54.Rep_state_icpsr dropped and 7 obs not used

note: 54.birthstate_icpsr != 0 predicts failure perfectly
      54.birthstate_icpsr dropped and 2 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 2 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 2 obs not used

note: 63.Rep_state_icpsr != 0 predicts failure perfectly
      63.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 1 obs not used

note: 35.Rep_state_icpsr omitted because of collinearity
note: 46.Rep_state_icpsr omitted because of collinearity
note: 67.Rep_state_icpsr omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-193.38285}  
Iteration 1:{space 3}log likelihood = {res:-114.03529}  
Iteration 2:{space 3}log likelihood = {res:-110.42464}  
Iteration 3:{space 3}log likelihood = {res:-110.25055}  
Iteration 4:{space 3}log likelihood = {res:-110.25016}  
Iteration 5:{space 3}log likelihood = {res:-110.25016}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       312
{txt}{col 49}LR chi2({res}57{txt}){col 67}= {res}    166.27
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-110.25016{txt}{col 49}Pseudo R2{col 67}= {res}    0.4299

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      born_instate{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0669679{col 32}{space 2} .0249256{col 43}{space 1}   -2.69{col 52}{space 3}0.007{col 60}{space 4}-.1158212{col 73}{space 3}-.0181146
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.4498724{col 32}{space 2}  .494149{col 43}{space 1}   -0.91{col 52}{space 3}0.363{col 60}{space 4}-1.418387{col 73}{space 3} .5186419
{txt}{space 13}Black {c |}{col 20}{res}{space 2} .4549799{col 32}{space 2} .8098427{col 43}{space 1}    0.56{col 52}{space 3}0.574{col 60}{space 4}-1.132283{col 73}{space 3} 2.042242
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .6576963{col 32}{space 2} .7924871{col 43}{space 1}    0.83{col 52}{space 3}0.407{col 60}{space 4}-.8955498{col 73}{space 3} 2.210942
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0006288{col 32}{space 2} .0253454{col 43}{space 1}   -0.02{col 52}{space 3}0.980{col 60}{space 4}-.0503049{col 73}{space 3} .0490473
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2}-.9624778{col 32}{space 2} 2.095088{col 43}{space 1}   -0.46{col 52}{space 3}0.646{col 60}{space 4}-5.068774{col 73}{space 3} 3.143818
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2} .0859117{col 32}{space 2} .0638748{col 43}{space 1}    1.35{col 52}{space 3}0.179{col 60}{space 4}-.0392807{col 73}{space 3}  .211104
{txt}{space 18} {c |}
{space 2}birthstate_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}3  {c |}{col 20}{res}{space 2}-.2316506{col 32}{space 2} 1.448412{col 43}{space 1}   -0.16{col 52}{space 3}0.873{col 60}{space 4}-3.070487{col 73}{space 3} 2.607185
{txt}{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}12  {c |}{col 20}{res}{space 2}-2.929755{col 32}{space 2} 1.800475{col 43}{space 1}   -1.63{col 52}{space 3}0.104{col 60}{space 4}-6.458621{col 73}{space 3} .5991119
{txt}{space 15}13  {c |}{col 20}{res}{space 2} -5.75383{col 32}{space 2} 1.902702{col 43}{space 1}   -3.02{col 52}{space 3}0.002{col 60}{space 4}-9.483057{col 73}{space 3}-2.024602
{txt}{space 15}14  {c |}{col 20}{res}{space 2}-3.553898{col 32}{space 2} 1.908994{col 43}{space 1}   -1.86{col 52}{space 3}0.063{col 60}{space 4}-7.295457{col 73}{space 3} .1876604
{txt}{space 15}21  {c |}{col 20}{res}{space 2}-1.292239{col 32}{space 2} 1.643683{col 43}{space 1}   -0.79{col 52}{space 3}0.432{col 60}{space 4}-4.513798{col 73}{space 3}  1.92932
{txt}{space 15}22  {c |}{col 20}{res}{space 2} -3.13574{col 32}{space 2} 2.344253{col 43}{space 1}   -1.34{col 52}{space 3}0.181{col 60}{space 4}-7.730391{col 73}{space 3} 1.458911
{txt}{space 15}23  {c |}{col 20}{res}{space 2} 2.543657{col 32}{space 2} 2.221531{col 43}{space 1}    1.15{col 52}{space 3}0.252{col 60}{space 4}-1.810465{col 73}{space 3} 6.897779
{txt}{space 15}24  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}25  {c |}{col 20}{res}{space 2}-2.472072{col 32}{space 2} 2.141544{col 43}{space 1}   -1.15{col 52}{space 3}0.248{col 60}{space 4} -6.66942{col 73}{space 3} 1.725277
{txt}{space 15}31  {c |}{col 20}{res}{space 2}-4.451689{col 32}{space 2} 2.673444{col 43}{space 1}   -1.67{col 52}{space 3}0.096{col 60}{space 4}-9.691543{col 73}{space 3} .7881647
{txt}{space 15}32  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}33  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}34  {c |}{col 20}{res}{space 2}-2.530901{col 32}{space 2}   2.5723{col 43}{space 1}   -0.98{col 52}{space 3}0.325{col 60}{space 4}-7.572516{col 73}{space 3} 2.510714
{txt}{space 15}35  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}37  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}40  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}41  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}42  {c |}{col 20}{res}{space 2}-1.986734{col 32}{space 2} 2.177323{col 43}{space 1}   -0.91{col 52}{space 3}0.362{col 60}{space 4}-6.254209{col 73}{space 3} 2.280742
{txt}{space 15}43  {c |}{col 20}{res}{space 2} 1.250907{col 32}{space 2} 1.966513{col 43}{space 1}    0.64{col 52}{space 3}0.525{col 60}{space 4}-2.603387{col 73}{space 3} 5.105202
{txt}{space 15}44  {c |}{col 20}{res}{space 2}-6.262903{col 32}{space 2} 2.556299{col 43}{space 1}   -2.45{col 52}{space 3}0.014{col 60}{space 4}-11.27316{col 73}{space 3}-1.252649
{txt}{space 15}45  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}46  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}47  {c |}{col 20}{res}{space 2}-8.886523{col 32}{space 2} 2.478275{col 43}{space 1}   -3.59{col 52}{space 3}0.000{col 60}{space 4}-13.74385{col 73}{space 3}-4.029193
{txt}{space 15}48  {c |}{col 20}{res}{space 2}-8.445544{col 32}{space 2} 2.514677{col 43}{space 1}   -3.36{col 52}{space 3}0.001{col 60}{space 4}-13.37422{col 73}{space 3}-3.516868
{txt}{space 15}49  {c |}{col 20}{res}{space 2} 1.693883{col 32}{space 2} 1.982262{col 43}{space 1}    0.85{col 52}{space 3}0.393{col 60}{space 4}-2.191279{col 73}{space 3} 5.579045
{txt}{space 15}51  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}52  {c |}{col 20}{res}{space 2}-1.516819{col 32}{space 2}   2.3547{col 43}{space 1}   -0.64{col 52}{space 3}0.519{col 60}{space 4}-6.131947{col 73}{space 3} 3.098309
{txt}{space 15}53  {c |}{col 20}{res}{space 2}-4.213484{col 32}{space 2} 2.705154{col 43}{space 1}   -1.56{col 52}{space 3}0.119{col 60}{space 4}-9.515489{col 73}{space 3} 1.088521
{txt}{space 15}54  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}56  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}61  {c |}{col 20}{res}{space 2}-2.149262{col 32}{space 2} 2.078857{col 43}{space 1}   -1.03{col 52}{space 3}0.301{col 60}{space 4}-6.223747{col 73}{space 3} 1.925223
{txt}{space 15}62  {c |}{col 20}{res}{space 2}-2.010154{col 32}{space 2}  2.00765{col 43}{space 1}   -1.00{col 52}{space 3}0.317{col 60}{space 4}-5.945075{col 73}{space 3} 1.924768
{txt}{space 15}65  {c |}{col 20}{res}{space 2} -2.47913{col 32}{space 2} 2.610348{col 43}{space 1}   -0.95{col 52}{space 3}0.342{col 60}{space 4}-7.595319{col 73}{space 3} 2.637059
{txt}{space 15}66  {c |}{col 20}{res}{space 2}-1.080887{col 32}{space 2}  2.21965{col 43}{space 1}   -0.49{col 52}{space 3}0.626{col 60}{space 4}-5.431321{col 73}{space 3} 3.269548
{txt}{space 15}67  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}71  {c |}{col 20}{res}{space 2} 4.333096{col 32}{space 2} 1.810904{col 43}{space 1}    2.39{col 52}{space 3}0.017{col 60}{space 4} .7837892{col 73}{space 3} 7.882402
{txt}{space 15}72  {c |}{col 20}{res}{space 2}-.3666467{col 32}{space 2} 2.710519{col 43}{space 1}   -0.14{col 52}{space 3}0.892{col 60}{space 4}-5.679166{col 73}{space 3} 4.945873
{txt}{space 15}73  {c |}{col 20}{res}{space 2} .7134098{col 32}{space 2} 2.060304{col 43}{space 1}    0.35{col 52}{space 3}0.729{col 60}{space 4}-3.324711{col 73}{space 3} 4.751531
{txt}{space 15}82  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}98  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}99  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}100  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}101  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}102  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}103  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}105  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}106  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}107  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}108  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}109  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}110  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}111  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}113  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}114  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}115  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}116  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}117  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}118  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 3}Rep_state_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}12  {c |}{col 20}{res}{space 2} 3.908596{col 32}{space 2} 1.868536{col 43}{space 1}    2.09{col 52}{space 3}0.036{col 60}{space 4} .2463336{col 73}{space 3} 7.570859
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{txt}{space 15}14  {c |}{col 20}{res}{space 2} 4.852016{col 32}{space 2} 1.887858{col 43}{space 1}    2.57{col 52}{space 3}0.010{col 60}{space 4} 1.151881{col 73}{space 3}  8.55215
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{txt}{space 15}23  {c |}{col 20}{res}{space 2}-.2358183{col 32}{space 2} 2.182678{col 43}{space 1}   -0.11{col 52}{space 3}0.914{col 60}{space 4}-4.513788{col 73}{space 3} 4.042152
{txt}{space 15}24  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}32  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}33  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{space 15}40  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}41  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{space 15}46  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}54  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}63  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}66  {c |}{col 20}{res}{space 2} .1333292{col 32}{space 2} 2.147768{col 43}{space 1}    0.06{col 52}{space 3}0.951{col 60}{space 4}-4.076219{col 73}{space 3} 4.342877
{txt}{space 15}67  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
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{txt}{space 15}72  {c |}{col 20}{res}{space 2}-2.548399{col 32}{space 2} 1.935165{col 43}{space 1}   -1.32{col 52}{space 3}0.188{col 60}{space 4}-6.341253{col 73}{space 3} 1.244454
{txt}{space 15}73  {c |}{col 20}{res}{space 2}-.2852195{col 32}{space 2} 1.980826{col 43}{space 1}   -0.14{col 52}{space 3}0.886{col 60}{space 4}-4.167568{col 73}{space 3} 3.597129
{txt}{space 15}82  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 3.938877{col 32}{space 2} 2.263867{col 43}{space 1}    1.74{col 52}{space 3}0.082{col 60}{space 4}-.4982197{col 73}{space 3} 8.375975
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_instate]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_instate]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}   10.06
{txt}{col 10}Prob > chi2 =  {res}  0.1852
{txt}
{com}. 
. *Republicans - Column 5
. logit born_instate AgeInteger Female Black Hispanic dpres i.birthstate_icpsr i.Rep_state_icpsr if congress<116 & party_code==200

{txt}note: 3.birthstate_icpsr != 0 predicts failure perfectly
      3.birthstate_icpsr dropped and 9 obs not used

note: 4.birthstate_icpsr != 0 predicts failure perfectly
      4.birthstate_icpsr dropped and 1 obs not used

note: 5.birthstate_icpsr != 0 predicts failure perfectly
      5.birthstate_icpsr dropped and 2 obs not used

note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 1 obs not used

note: 61.birthstate_icpsr != 0 predicts success perfectly
      61.birthstate_icpsr dropped and 4 obs not used

note: 64.birthstate_icpsr != 0 predicts success perfectly
      64.birthstate_icpsr dropped and 2 obs not used

note: 65.birthstate_icpsr != 0 predicts success perfectly
      65.birthstate_icpsr dropped and 3 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 5 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 1 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 2 obs not used

note: 104.birthstate_icpsr != 0 predicts failure perfectly
      104.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 1 obs not used

note: 112.birthstate_icpsr != 0 predicts failure perfectly
      112.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 1 obs not used

note: 2.Rep_state_icpsr != 0 predicts success perfectly
      2.Rep_state_icpsr dropped and 1 obs not used

note: 2.birthstate_icpsr != 0 predicts failure perfectly
      2.birthstate_icpsr dropped and 1 obs not used

note: 4.Rep_state_icpsr != 0 predicts failure perfectly
      4.Rep_state_icpsr dropped and 2 obs not used

note: 31.Rep_state_icpsr != 0 predicts success perfectly
      31.Rep_state_icpsr dropped and 7 obs not used

note: 31.birthstate_icpsr != 0 predicts failure perfectly
      31.birthstate_icpsr dropped and 7 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 2 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 3 obs not used

note: 46.Rep_state_icpsr != 0 predicts success perfectly
      46.Rep_state_icpsr dropped and 6 obs not used

note: 46.birthstate_icpsr != 0 predicts failure perfectly
      46.birthstate_icpsr dropped and 2 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 3 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 3 obs not used

note: 61.Rep_state_icpsr != 0 predicts failure perfectly
      61.Rep_state_icpsr dropped and 9 obs not used

note: 62.birthstate_icpsr != 0 predicts success perfectly
      62.birthstate_icpsr dropped and 5 obs not used

note: 67.birthstate_icpsr != 0 predicts success perfectly
      67.birthstate_icpsr dropped and 5 obs not used

note: 62.Rep_state_icpsr != 0 predicts failure perfectly
      62.Rep_state_icpsr dropped and 6 obs not used

note: 32.birthstate_icpsr != 0 predicts success perfectly
      32.birthstate_icpsr dropped and 7 obs not used

note: 66.birthstate_icpsr != 0 predicts success perfectly
      66.birthstate_icpsr dropped and 1 obs not used

note: 32.Rep_state_icpsr != 0 predicts failure perfectly
      32.Rep_state_icpsr dropped and 2 obs not used

note: 64.Rep_state_icpsr != 0 predicts failure perfectly
      64.Rep_state_icpsr dropped and 2 obs not used

note: 65.Rep_state_icpsr != 0 predicts failure perfectly
      65.Rep_state_icpsr dropped and 2 obs not used

note: 66.Rep_state_icpsr != 0 predicts failure perfectly
      66.Rep_state_icpsr dropped and 1 obs not used

note: 67.Rep_state_icpsr != 0 predicts failure perfectly
      67.Rep_state_icpsr dropped and 2 obs not used

note: 72.Rep_state_icpsr != 0 predicts success perfectly
      72.Rep_state_icpsr dropped and 1 obs not used

note: 72.birthstate_icpsr != 0 predicts failure perfectly
      72.birthstate_icpsr dropped and 1 obs not used

note: 81.Rep_state_icpsr != 0 predicts failure perfectly
      81.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 1 obs not used

note: 11.Rep_state_icpsr omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-263.31747}  
Iteration 1:{space 3}log likelihood = {res:-153.26879}  
Iteration 2:{space 3}log likelihood = {res:-149.16113}  
Iteration 3:{space 3}log likelihood = {res:-148.72185}  
Iteration 4:{space 3}log likelihood = {res:-148.71533}  
Iteration 5:{space 3}log likelihood = {res:-148.71531}  
Iteration 6:{space 3}log likelihood = {res:-148.71531}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       425
{txt}{col 49}LR chi2({res}63{txt}){col 67}= {res}    229.20
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-148.71531{txt}{col 49}Pseudo R2{col 67}= {res}    0.4352

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}    born_instate{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}AgeInteger {c |}{col 18}{res}{space 2} -.003101{col 30}{space 2} .0171617{col 41}{space 1}   -0.18{col 50}{space 3}0.857{col 58}{space 4}-.0367372{col 71}{space 3} .0305353
{txt}{space 10}Female {c |}{col 18}{res}{space 2}-.4354672{col 30}{space 2} .5971103{col 41}{space 1}   -0.73{col 50}{space 3}0.466{col 58}{space 4}-1.605782{col 71}{space 3} .7348474
{txt}{space 11}Black {c |}{col 18}{res}{space 2}-.5978774{col 30}{space 2} 1.437384{col 41}{space 1}   -0.42{col 50}{space 3}0.677{col 58}{space 4}-3.415098{col 71}{space 3} 2.219343
{txt}{space 8}Hispanic {c |}{col 18}{res}{space 2}-1.045625{col 30}{space 2} 1.010845{col 41}{space 1}   -1.03{col 50}{space 3}0.301{col 58}{space 4}-3.026844{col 71}{space 3} .9355945
{txt}{space 11}dpres {c |}{col 18}{res}{space 2} .0239428{col 30}{space 2} .0233125{col 41}{space 1}    1.03{col 50}{space 3}0.304{col 58}{space 4}-.0217489{col 71}{space 3} .0696344
{txt}{space 16} {c |}
birthstate_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}3  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}4  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}5  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2} 3.752696{col 30}{space 2} 2.159252{col 41}{space 1}    1.74{col 50}{space 3}0.082{col 58}{space 4}-.4793601{col 71}{space 3} 7.984752
{txt}{space 13}13  {c |}{col 18}{res}{space 2} -.956891{col 30}{space 2} 1.731514{col 41}{space 1}   -0.55{col 50}{space 3}0.581{col 58}{space 4}-4.350596{col 71}{space 3} 2.436814
{txt}{space 13}14  {c |}{col 18}{res}{space 2} .1556604{col 30}{space 2} 1.777469{col 41}{space 1}    0.09{col 50}{space 3}0.930{col 58}{space 4}-3.328114{col 71}{space 3} 3.639435
{txt}{space 13}21  {c |}{col 18}{res}{space 2}-6.864702{col 30}{space 2} 2.451689{col 41}{space 1}   -2.80{col 50}{space 3}0.005{col 58}{space 4}-11.66992{col 71}{space 3} -2.05948
{txt}{space 13}22  {c |}{col 18}{res}{space 2} 1.582335{col 30}{space 2} 2.052364{col 41}{space 1}    0.77{col 50}{space 3}0.441{col 58}{space 4}-2.440224{col 71}{space 3} 5.604894
{txt}{space 13}23  {c |}{col 18}{res}{space 2}-2.050713{col 30}{space 2} 2.197478{col 41}{space 1}   -0.93{col 50}{space 3}0.351{col 58}{space 4}-6.357691{col 71}{space 3} 2.256265
{txt}{space 13}24  {c |}{col 18}{res}{space 2} .1078436{col 30}{space 2} 1.928644{col 41}{space 1}    0.06{col 50}{space 3}0.955{col 58}{space 4} -3.67223{col 71}{space 3} 3.887917
{txt}{space 13}25  {c |}{col 18}{res}{space 2}  .255422{col 30}{space 2} 4.038586{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-7.660062{col 71}{space 3} 8.170905
{txt}{space 13}31  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}32  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}33  {c |}{col 18}{res}{space 2}-7.966058{col 30}{space 2} 3.207261{col 41}{space 1}   -2.48{col 50}{space 3}0.013{col 58}{space 4}-14.25217{col 71}{space 3}-1.679943
{txt}{space 13}34  {c |}{col 18}{res}{space 2} .9920482{col 30}{space 2} 1.968681{col 41}{space 1}    0.50{col 50}{space 3}0.614{col 58}{space 4}-2.866496{col 71}{space 3} 4.850592
{txt}{space 13}35  {c |}{col 18}{res}{space 2} 2.296732{col 30}{space 2} 2.740125{col 41}{space 1}    0.84{col 50}{space 3}0.402{col 58}{space 4}-3.073814{col 71}{space 3} 7.667278
{txt}{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}37  {c |}{col 18}{res}{space 2}-1.213153{col 30}{space 2} 3.484845{col 41}{space 1}   -0.35{col 50}{space 3}0.728{col 58}{space 4}-8.043324{col 71}{space 3} 5.617019
{txt}{space 13}40  {c |}{col 18}{res}{space 2} 3.039689{col 30}{space 2} 2.030494{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.9400067{col 71}{space 3} 7.019384
{txt}{space 13}41  {c |}{col 18}{res}{space 2} 3.224106{col 30}{space 2} 2.260578{col 41}{space 1}    1.43{col 50}{space 3}0.154{col 58}{space 4}-1.206546{col 71}{space 3} 7.654758
{txt}{space 13}42  {c |}{col 18}{res}{space 2} 4.338198{col 30}{space 2} 2.262627{col 41}{space 1}    1.92{col 50}{space 3}0.055{col 58}{space 4}-.0964689{col 71}{space 3} 8.772865
{txt}{space 13}43  {c |}{col 18}{res}{space 2} 4.759983{col 30}{space 2} 1.948236{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .9415106{col 71}{space 3} 8.578455
{txt}{space 13}44  {c |}{col 18}{res}{space 2} 3.416287{col 30}{space 2} 2.035804{col 41}{space 1}    1.68{col 50}{space 3}0.093{col 58}{space 4} -.573815{col 71}{space 3} 7.406389
{txt}{space 13}45  {c |}{col 18}{res}{space 2}-1.912517{col 30}{space 2} 2.771427{col 41}{space 1}   -0.69{col 50}{space 3}0.490{col 58}{space 4}-7.344415{col 71}{space 3}  3.51938
{txt}{space 13}46  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}47  {c |}{col 18}{res}{space 2} 3.311229{col 30}{space 2} 2.019266{col 41}{space 1}    1.64{col 50}{space 3}0.101{col 58}{space 4}-.6464604{col 71}{space 3} 7.268918
{txt}{space 13}48  {c |}{col 18}{res}{space 2} 6.940371{col 30}{space 2} 2.514358{col 41}{space 1}    2.76{col 50}{space 3}0.006{col 58}{space 4} 2.012319{col 71}{space 3} 11.86842
{txt}{space 13}49  {c |}{col 18}{res}{space 2} 3.496586{col 30}{space 2} 1.934204{col 41}{space 1}    1.81{col 50}{space 3}0.071{col 58}{space 4} -.294383{col 71}{space 3} 7.287556
{txt}{space 13}51  {c |}{col 18}{res}{space 2} 2.684799{col 30}{space 2} 2.352004{col 41}{space 1}    1.14{col 50}{space 3}0.254{col 58}{space 4}-1.925044{col 71}{space 3} 7.294643
{txt}{space 13}52  {c |}{col 18}{res}{space 2}-.0222469{col 30}{space 2} 2.284985{col 41}{space 1}   -0.01{col 50}{space 3}0.992{col 58}{space 4}-4.500735{col 71}{space 3} 4.456241
{txt}{space 13}53  {c |}{col 18}{res}{space 2} 6.388953{col 30}{space 2} 2.435808{col 41}{space 1}    2.62{col 50}{space 3}0.009{col 58}{space 4} 1.614857{col 71}{space 3} 11.16305
{txt}{space 13}54  {c |}{col 18}{res}{space 2} 1.488859{col 30}{space 2} 1.996765{col 41}{space 1}    0.75{col 50}{space 3}0.456{col 58}{space 4}-2.424727{col 71}{space 3} 5.402446
{txt}{space 13}56  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}61  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}62  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}63  {c |}{col 18}{res}{space 2} 1.404088{col 30}{space 2}  2.31284{col 41}{space 1}    0.61{col 50}{space 3}0.544{col 58}{space 4}-3.128996{col 71}{space 3} 5.937172
{txt}{space 13}64  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}65  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}66  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}67  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}68  {c |}{col 18}{res}{space 2} 2.339966{col 30}{space 2} 2.484703{col 41}{space 1}    0.94{col 50}{space 3}0.346{col 58}{space 4}-2.529962{col 71}{space 3} 7.209894
{txt}{space 13}71  {c |}{col 18}{res}{space 2} 3.163673{col 30}{space 2} 1.787137{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.3390514{col 71}{space 3} 6.666397
{txt}{space 13}72  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}73  {c |}{col 18}{res}{space 2}  .740068{col 30}{space 2} 2.101049{col 41}{space 1}    0.35{col 50}{space 3}0.725{col 58}{space 4}-3.377911{col 71}{space 3} 4.858048
{txt}{space 13}98  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}100  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}101  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}104  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}105  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}112  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}115  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 12}118  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 1}Rep_state_icpsr {c |}
{space 14}2  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 14}4  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}11  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}12  {c |}{col 18}{res}{space 2}-1.998373{col 30}{space 2} 2.093092{col 41}{space 1}   -0.95{col 50}{space 3}0.340{col 58}{space 4}-6.100757{col 71}{space 3} 2.104012
{txt}{space 13}13  {c |}{col 18}{res}{space 2} 3.057678{col 30}{space 2} 1.837765{col 41}{space 1}    1.66{col 50}{space 3}0.096{col 58}{space 4}-.5442747{col 71}{space 3} 6.659632
{txt}{space 13}14  {c |}{col 18}{res}{space 2}   1.2957{col 30}{space 2} 1.977341{col 41}{space 1}    0.66{col 50}{space 3}0.512{col 58}{space 4}-2.579816{col 71}{space 3} 5.171217
{txt}{space 13}21  {c |}{col 18}{res}{space 2} 9.615227{col 30}{space 2} 2.741476{col 41}{space 1}    3.51{col 50}{space 3}0.000{col 58}{space 4} 4.242033{col 71}{space 3} 14.98842
{txt}{space 13}22  {c |}{col 18}{res}{space 2} .0758484{col 30}{space 2} 2.183322{col 41}{space 1}    0.03{col 50}{space 3}0.972{col 58}{space 4}-4.203383{col 71}{space 3}  4.35508
{txt}{space 13}23  {c |}{col 18}{res}{space 2} 5.139017{col 30}{space 2} 2.503602{col 41}{space 1}    2.05{col 50}{space 3}0.040{col 58}{space 4} .2320474{col 71}{space 3} 10.04599
{txt}{space 13}24  {c |}{col 18}{res}{space 2} 1.587027{col 30}{space 2} 2.158428{col 41}{space 1}    0.74{col 50}{space 3}0.462{col 58}{space 4}-2.643414{col 71}{space 3} 5.817469
{txt}{space 13}25  {c |}{col 18}{res}{space 2} 4.133398{col 30}{space 2}  4.13997{col 41}{space 1}    1.00{col 50}{space 3}0.318{col 58}{space 4}-3.980795{col 71}{space 3} 12.24759
{txt}{space 13}31  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}32  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}33  {c |}{col 18}{res}{space 2} -2.79777{col 30}{space 2} 2.393837{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-7.489604{col 71}{space 3} 1.894063
{txt}{space 13}34  {c |}{col 18}{res}{space 2} .8617017{col 30}{space 2} 2.133106{col 41}{space 1}    0.40{col 50}{space 3}0.686{col 58}{space 4}-3.319109{col 71}{space 3} 5.042513
{txt}{space 13}35  {c |}{col 18}{res}{space 2} .6145286{col 30}{space 2}  3.07463{col 41}{space 1}    0.20{col 50}{space 3}0.842{col 58}{space 4}-5.411636{col 71}{space 3} 6.640693
{txt}{space 13}36  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}37  {c |}{col 18}{res}{space 2}   4.4434{col 30}{space 2} 3.672714{col 41}{space 1}    1.21{col 50}{space 3}0.226{col 58}{space 4}-2.754988{col 71}{space 3} 11.64179
{txt}{space 13}40  {c |}{col 18}{res}{space 2}-3.638223{col 30}{space 2} 2.160251{col 41}{space 1}   -1.68{col 50}{space 3}0.092{col 58}{space 4}-7.872237{col 71}{space 3} .5957903
{txt}{space 13}41  {c |}{col 18}{res}{space 2}-1.579932{col 30}{space 2} 2.450193{col 41}{space 1}   -0.64{col 50}{space 3}0.519{col 58}{space 4}-6.382222{col 71}{space 3} 3.222358
{txt}{space 13}42  {c |}{col 18}{res}{space 2}-3.376652{col 30}{space 2} 2.377449{col 41}{space 1}   -1.42{col 50}{space 3}0.156{col 58}{space 4}-8.036366{col 71}{space 3} 1.283061
{txt}{space 13}43  {c |}{col 18}{res}{space 2} -3.50355{col 30}{space 2} 2.046948{col 41}{space 1}   -1.71{col 50}{space 3}0.087{col 58}{space 4}-7.515493{col 71}{space 3}  .508394
{txt}{space 13}44  {c |}{col 18}{res}{space 2}-1.798251{col 30}{space 2} 2.239507{col 41}{space 1}   -0.80{col 50}{space 3}0.422{col 58}{space 4}-6.187604{col 71}{space 3} 2.591103
{txt}{space 13}45  {c |}{col 18}{res}{space 2}  5.82332{col 30}{space 2}  2.91467{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .1106716{col 71}{space 3} 11.53597
{txt}{space 13}46  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}47  {c |}{col 18}{res}{space 2}-2.672826{col 30}{space 2} 2.155517{col 41}{space 1}   -1.24{col 50}{space 3}0.215{col 58}{space 4}-6.897562{col 71}{space 3} 1.551909
{txt}{space 13}48  {c |}{col 18}{res}{space 2}-4.620251{col 30}{space 2}  2.42287{col 41}{space 1}   -1.91{col 50}{space 3}0.057{col 58}{space 4}-9.368988{col 71}{space 3}  .128487
{txt}{space 13}49  {c |}{col 18}{res}{space 2}-.8620462{col 30}{space 2} 2.125025{col 41}{space 1}   -0.41{col 50}{space 3}0.685{col 58}{space 4}-5.027019{col 71}{space 3} 3.302927
{txt}{space 13}51  {c |}{col 18}{res}{space 2}-1.490541{col 30}{space 2}  2.45011{col 41}{space 1}   -0.61{col 50}{space 3}0.543{col 58}{space 4}-6.292668{col 71}{space 3} 3.311586
{txt}{space 13}52  {c |}{col 18}{res}{space 2}-3.403481{col 30}{space 2} 2.539887{col 41}{space 1}   -1.34{col 50}{space 3}0.180{col 58}{space 4}-8.381568{col 71}{space 3} 1.574607
{txt}{space 13}53  {c |}{col 18}{res}{space 2}-4.673639{col 30}{space 2} 2.369756{col 41}{space 1}   -1.97{col 50}{space 3}0.049{col 58}{space 4}-9.318276{col 71}{space 3}-.0290031
{txt}{space 13}54  {c |}{col 18}{res}{space 2}-.2583398{col 30}{space 2} 2.143969{col 41}{space 1}   -0.12{col 50}{space 3}0.904{col 58}{space 4}-4.460441{col 71}{space 3} 3.943762
{txt}{space 13}56  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}61  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}62  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}63  {c |}{col 18}{res}{space 2}-.1306658{col 30}{space 2} 2.533119{col 41}{space 1}   -0.05{col 50}{space 3}0.959{col 58}{space 4}-5.095488{col 71}{space 3} 4.834156
{txt}{space 13}64  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}65  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}66  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}67  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}68  {c |}{col 18}{res}{space 2}-2.319604{col 30}{space 2} 2.654955{col 41}{space 1}   -0.87{col 50}{space 3}0.382{col 58}{space 4}-7.523221{col 71}{space 3} 2.884012
{txt}{space 13}71  {c |}{col 18}{res}{space 2}-1.429393{col 30}{space 2} 1.929339{col 41}{space 1}   -0.74{col 50}{space 3}0.459{col 58}{space 4}-5.210828{col 71}{space 3} 2.352042
{txt}{space 13}72  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}73  {c |}{col 18}{res}{space 2} .4582289{col 30}{space 2} 2.510497{col 41}{space 1}    0.18{col 50}{space 3}0.855{col 58}{space 4}-4.462255{col 71}{space 3} 5.378712
{txt}{space 13}81  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 13}82  {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (empty)
{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2}-.7015388{col 30}{space 2} 2.359286{col 41}{space 1}   -0.30{col 50}{space 3}0.766{col 58}{space 4}-5.325655{col 71}{space 3} 3.922577
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    2.40
{txt}{col 10}Prob > chi2 =  {res}  0.7911
{txt}
{com}. 
. *Republicans - Column 6
. logit born_instate AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.birthstate_icpsr i.Rep_state_icpsr if congress<116 & party_code==200

{txt}note: 3.birthstate_icpsr != 0 predicts failure perfectly
      3.birthstate_icpsr dropped and 9 obs not used

note: 4.birthstate_icpsr != 0 predicts failure perfectly
      4.birthstate_icpsr dropped and 1 obs not used

note: 5.birthstate_icpsr != 0 predicts failure perfectly
      5.birthstate_icpsr dropped and 2 obs not used

note: 11.birthstate_icpsr != 0 predicts success perfectly
      11.birthstate_icpsr dropped and 1 obs not used

note: 61.birthstate_icpsr != 0 predicts success perfectly
      61.birthstate_icpsr dropped and 4 obs not used

note: 64.birthstate_icpsr != 0 predicts success perfectly
      64.birthstate_icpsr dropped and 2 obs not used

note: 65.birthstate_icpsr != 0 predicts success perfectly
      65.birthstate_icpsr dropped and 3 obs not used

note: 98.birthstate_icpsr != 0 predicts failure perfectly
      98.birthstate_icpsr dropped and 5 obs not used

note: 100.birthstate_icpsr != 0 predicts failure perfectly
      100.birthstate_icpsr dropped and 1 obs not used

note: 101.birthstate_icpsr != 0 predicts failure perfectly
      101.birthstate_icpsr dropped and 2 obs not used

note: 104.birthstate_icpsr != 0 predicts failure perfectly
      104.birthstate_icpsr dropped and 1 obs not used

note: 105.birthstate_icpsr != 0 predicts failure perfectly
      105.birthstate_icpsr dropped and 1 obs not used

note: 112.birthstate_icpsr != 0 predicts failure perfectly
      112.birthstate_icpsr dropped and 1 obs not used

note: 115.birthstate_icpsr != 0 predicts failure perfectly
      115.birthstate_icpsr dropped and 1 obs not used

note: 118.birthstate_icpsr != 0 predicts failure perfectly
      118.birthstate_icpsr dropped and 1 obs not used

note: 2.Rep_state_icpsr != 0 predicts success perfectly
      2.Rep_state_icpsr dropped and 1 obs not used

note: 2.birthstate_icpsr != 0 predicts failure perfectly
      2.birthstate_icpsr dropped and 1 obs not used

note: 4.Rep_state_icpsr != 0 predicts failure perfectly
      4.Rep_state_icpsr dropped and 2 obs not used

note: 31.Rep_state_icpsr != 0 predicts success perfectly
      31.Rep_state_icpsr dropped and 7 obs not used

note: 31.birthstate_icpsr != 0 predicts failure perfectly
      31.birthstate_icpsr dropped and 7 obs not used

note: 36.Rep_state_icpsr != 0 predicts success perfectly
      36.Rep_state_icpsr dropped and 2 obs not used

note: 36.birthstate_icpsr != 0 predicts failure perfectly
      36.birthstate_icpsr dropped and 3 obs not used

note: 46.Rep_state_icpsr != 0 predicts success perfectly
      46.Rep_state_icpsr dropped and 6 obs not used

note: 46.birthstate_icpsr != 0 predicts failure perfectly
      46.birthstate_icpsr dropped and 2 obs not used

note: 56.Rep_state_icpsr != 0 predicts success perfectly
      56.Rep_state_icpsr dropped and 3 obs not used

note: 56.birthstate_icpsr != 0 predicts failure perfectly
      56.birthstate_icpsr dropped and 3 obs not used

note: 61.Rep_state_icpsr != 0 predicts failure perfectly
      61.Rep_state_icpsr dropped and 9 obs not used

note: 62.birthstate_icpsr != 0 predicts success perfectly
      62.birthstate_icpsr dropped and 5 obs not used

note: 67.birthstate_icpsr != 0 predicts success perfectly
      67.birthstate_icpsr dropped and 5 obs not used

note: 62.Rep_state_icpsr != 0 predicts failure perfectly
      62.Rep_state_icpsr dropped and 6 obs not used

note: 32.birthstate_icpsr != 0 predicts success perfectly
      32.birthstate_icpsr dropped and 7 obs not used

note: 66.birthstate_icpsr != 0 predicts success perfectly
      66.birthstate_icpsr dropped and 1 obs not used

note: 32.Rep_state_icpsr != 0 predicts failure perfectly
      32.Rep_state_icpsr dropped and 2 obs not used

note: 64.Rep_state_icpsr != 0 predicts failure perfectly
      64.Rep_state_icpsr dropped and 2 obs not used

note: 65.Rep_state_icpsr != 0 predicts failure perfectly
      65.Rep_state_icpsr dropped and 2 obs not used

note: 66.Rep_state_icpsr != 0 predicts failure perfectly
      66.Rep_state_icpsr dropped and 1 obs not used

note: 67.Rep_state_icpsr != 0 predicts failure perfectly
      67.Rep_state_icpsr dropped and 2 obs not used

note: 72.Rep_state_icpsr != 0 predicts success perfectly
      72.Rep_state_icpsr dropped and 1 obs not used

note: 72.birthstate_icpsr != 0 predicts failure perfectly
      72.birthstate_icpsr dropped and 1 obs not used

note: 81.Rep_state_icpsr != 0 predicts failure perfectly
      81.Rep_state_icpsr dropped and 1 obs not used

note: 82.Rep_state_icpsr != 0 predicts failure perfectly
      82.Rep_state_icpsr dropped and 1 obs not used

note: 11.Rep_state_icpsr omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-262.94502}  
Iteration 1:{space 3}log likelihood = {res:-150.81006}  
Iteration 2:{space 3}log likelihood = {res:-146.43153}  
Iteration 3:{space 3}log likelihood = {res:-145.95861}  
Iteration 4:{space 3}log likelihood = {res:-145.95103}  
Iteration 5:{space 3}log likelihood = {res:-145.95101}  
Iteration 6:{space 3}log likelihood = {res:-145.95101}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       424
{txt}{col 49}LR chi2({res}65{txt}){col 67}= {res}    233.99
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-145.95101{txt}{col 49}Pseudo R2{col 67}= {res}    0.4449

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}      born_instate{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0190227{col 32}{space 2} .0200334{col 43}{space 1}   -0.95{col 52}{space 3}0.342{col 60}{space 4}-.0582874{col 73}{space 3}  .020242
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.4741849{col 32}{space 2} .6103629{col 43}{space 1}   -0.78{col 52}{space 3}0.437{col 60}{space 4}-1.670474{col 73}{space 3} .7221044
{txt}{space 13}Black {c |}{col 20}{res}{space 2}-.7792115{col 32}{space 2} 1.467449{col 43}{space 1}   -0.53{col 52}{space 3}0.595{col 60}{space 4}-3.655359{col 73}{space 3} 2.096936
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2}-1.424708{col 32}{space 2} 1.029356{col 43}{space 1}   -1.38{col 52}{space 3}0.166{col 60}{space 4}-3.442208{col 73}{space 3}  .592792
{txt}{space 13}dpres {c |}{col 20}{res}{space 2} .0150789{col 32}{space 2} .0237349{col 43}{space 1}    0.64{col 52}{space 3}0.525{col 60}{space 4}-.0314407{col 73}{space 3} .0615985
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2}-2.376192{col 32}{space 2} 1.399766{col 43}{space 1}   -1.70{col 52}{space 3}0.090{col 60}{space 4}-5.119684{col 73}{space 3} .3672991
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2} .0779072{col 32}{space 2} .0654765{col 43}{space 1}    1.19{col 52}{space 3}0.234{col 60}{space 4}-.0504244{col 73}{space 3} .2062388
{txt}{space 18} {c |}
{space 2}birthstate_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}12  {c |}{col 20}{res}{space 2} 3.519204{col 32}{space 2} 2.175103{col 43}{space 1}    1.62{col 52}{space 3}0.106{col 60}{space 4}-.7439193{col 73}{space 3} 7.782327
{txt}{space 15}13  {c |}{col 20}{res}{space 2}-.5909987{col 32}{space 2} 1.770795{col 43}{space 1}   -0.33{col 52}{space 3}0.739{col 60}{space 4}-4.061693{col 73}{space 3} 2.879696
{txt}{space 15}14  {c |}{col 20}{res}{space 2} .0820005{col 32}{space 2} 1.813531{col 43}{space 1}    0.05{col 52}{space 3}0.964{col 60}{space 4}-3.472454{col 73}{space 3} 3.636455
{txt}{space 15}21  {c |}{col 20}{res}{space 2}-6.653771{col 32}{space 2} 2.474141{col 43}{space 1}   -2.69{col 52}{space 3}0.007{col 60}{space 4}  -11.503{col 73}{space 3}-1.804544
{txt}{space 15}22  {c |}{col 20}{res}{space 2} 1.683474{col 32}{space 2}  2.09738{col 43}{space 1}    0.80{col 52}{space 3}0.422{col 60}{space 4}-2.427315{col 73}{space 3} 5.794263
{txt}{space 15}23  {c |}{col 20}{res}{space 2}-1.836817{col 32}{space 2} 2.226586{col 43}{space 1}   -0.82{col 52}{space 3}0.409{col 60}{space 4}-6.200845{col 73}{space 3}  2.52721
{txt}{space 15}24  {c |}{col 20}{res}{space 2} .0514635{col 32}{space 2} 1.977521{col 43}{space 1}    0.03{col 52}{space 3}0.979{col 60}{space 4}-3.824406{col 73}{space 3} 3.927333
{txt}{space 15}25  {c |}{col 20}{res}{space 2} .6041851{col 32}{space 2} 3.887182{col 43}{space 1}    0.16{col 52}{space 3}0.876{col 60}{space 4}-7.014552{col 73}{space 3} 8.222922
{txt}{space 15}31  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}32  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}33  {c |}{col 20}{res}{space 2}-8.027488{col 32}{space 2} 3.290796{col 43}{space 1}   -2.44{col 52}{space 3}0.015{col 60}{space 4}-14.47733{col 73}{space 3}-1.577647
{txt}{space 15}34  {c |}{col 20}{res}{space 2} 1.061256{col 32}{space 2}  2.03835{col 43}{space 1}    0.52{col 52}{space 3}0.603{col 60}{space 4}-2.933837{col 73}{space 3} 5.056349
{txt}{space 15}35  {c |}{col 20}{res}{space 2} 2.402314{col 32}{space 2} 2.752028{col 43}{space 1}    0.87{col 52}{space 3}0.383{col 60}{space 4}-2.991563{col 73}{space 3}  7.79619
{txt}{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}37  {c |}{col 20}{res}{space 2}-1.459912{col 32}{space 2} 3.332367{col 43}{space 1}   -0.44{col 52}{space 3}0.661{col 60}{space 4}-7.991231{col 73}{space 3} 5.071406
{txt}{space 15}40  {c |}{col 20}{res}{space 2} 2.932865{col 32}{space 2}  2.04975{col 43}{space 1}    1.43{col 52}{space 3}0.152{col 60}{space 4}-1.084571{col 73}{space 3} 6.950301
{txt}{space 15}41  {c |}{col 20}{res}{space 2} 3.485456{col 32}{space 2} 2.299152{col 43}{space 1}    1.52{col 52}{space 3}0.130{col 60}{space 4}-1.020799{col 73}{space 3} 7.991712
{txt}{space 15}42  {c |}{col 20}{res}{space 2} 4.100509{col 32}{space 2} 2.269646{col 43}{space 1}    1.81{col 52}{space 3}0.071{col 60}{space 4}-.3479161{col 73}{space 3} 8.548934
{txt}{space 15}43  {c |}{col 20}{res}{space 2} 4.710403{col 32}{space 2} 1.964621{col 43}{space 1}    2.40{col 52}{space 3}0.017{col 60}{space 4} .8598174{col 73}{space 3} 8.560988
{txt}{space 15}44  {c |}{col 20}{res}{space 2} 3.672365{col 32}{space 2} 2.077954{col 43}{space 1}    1.77{col 52}{space 3}0.077{col 60}{space 4}-.4003507{col 73}{space 3} 7.745081
{txt}{space 15}45  {c |}{col 20}{res}{space 2}-1.874689{col 32}{space 2} 2.789658{col 43}{space 1}   -0.67{col 52}{space 3}0.502{col 60}{space 4}-7.342318{col 73}{space 3} 3.592939
{txt}{space 15}46  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}47  {c |}{col 20}{res}{space 2} 3.035238{col 32}{space 2} 2.038463{col 43}{space 1}    1.49{col 52}{space 3}0.136{col 60}{space 4}-.9600758{col 73}{space 3} 7.030552
{txt}{space 15}48  {c |}{col 20}{res}{space 2}  7.00696{col 32}{space 2}  2.52348{col 43}{space 1}    2.78{col 52}{space 3}0.005{col 60}{space 4}  2.06103{col 73}{space 3} 11.95289
{txt}{space 15}49  {c |}{col 20}{res}{space 2} 3.433283{col 32}{space 2} 1.981182{col 43}{space 1}    1.73{col 52}{space 3}0.083{col 60}{space 4}-.4497623{col 73}{space 3} 7.316329
{txt}{space 15}51  {c |}{col 20}{res}{space 2} 2.759178{col 32}{space 2} 2.408487{col 43}{space 1}    1.15{col 52}{space 3}0.252{col 60}{space 4} -1.96137{col 73}{space 3} 7.479726
{txt}{space 15}52  {c |}{col 20}{res}{space 2}-.0765227{col 32}{space 2} 2.381366{col 43}{space 1}   -0.03{col 52}{space 3}0.974{col 60}{space 4}-4.743914{col 73}{space 3} 4.590869
{txt}{space 15}53  {c |}{col 20}{res}{space 2} 6.433688{col 32}{space 2} 2.455707{col 43}{space 1}    2.62{col 52}{space 3}0.009{col 60}{space 4}  1.62059{col 73}{space 3} 11.24679
{txt}{space 15}54  {c |}{col 20}{res}{space 2} 1.634735{col 32}{space 2} 2.045099{col 43}{space 1}    0.80{col 52}{space 3}0.424{col 60}{space 4}-2.373584{col 73}{space 3} 5.643055
{txt}{space 15}56  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}61  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}62  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}63  {c |}{col 20}{res}{space 2} .8100027{col 32}{space 2} 2.387983{col 43}{space 1}    0.34{col 52}{space 3}0.734{col 60}{space 4}-3.870357{col 73}{space 3} 5.490362
{txt}{space 15}64  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}65  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}66  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}67  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}68  {c |}{col 20}{res}{space 2} 2.975145{col 32}{space 2} 2.552051{col 43}{space 1}    1.17{col 52}{space 3}0.244{col 60}{space 4}-2.026782{col 73}{space 3} 7.977072
{txt}{space 15}71  {c |}{col 20}{res}{space 2} 3.280414{col 32}{space 2} 1.863911{col 43}{space 1}    1.76{col 52}{space 3}0.078{col 60}{space 4}-.3727842{col 73}{space 3} 6.933612
{txt}{space 15}72  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}73  {c |}{col 20}{res}{space 2} .5002213{col 32}{space 2} 2.173587{col 43}{space 1}    0.23{col 52}{space 3}0.818{col 60}{space 4}-3.759931{col 73}{space 3} 4.760374
{txt}{space 15}98  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}100  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}101  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}104  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}105  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}112  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}115  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 14}118  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 3}Rep_state_icpsr {c |}
{space 16}2  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}11  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}12  {c |}{col 20}{res}{space 2}-1.492601{col 32}{space 2} 2.092118{col 43}{space 1}   -0.71{col 52}{space 3}0.476{col 60}{space 4}-5.593077{col 73}{space 3} 2.607875
{txt}{space 15}13  {c |}{col 20}{res}{space 2} 3.259246{col 32}{space 2} 1.873493{col 43}{space 1}    1.74{col 52}{space 3}0.082{col 60}{space 4}-.4127333{col 73}{space 3} 6.931226
{txt}{space 15}14  {c |}{col 20}{res}{space 2} 1.888136{col 32}{space 2} 2.018561{col 43}{space 1}    0.94{col 52}{space 3}0.350{col 60}{space 4}-2.068171{col 73}{space 3} 5.844442
{txt}{space 15}21  {c |}{col 20}{res}{space 2} 10.09215{col 32}{space 2} 2.781951{col 43}{space 1}    3.63{col 52}{space 3}0.000{col 60}{space 4} 4.639622{col 73}{space 3} 15.54467
{txt}{space 15}22  {c |}{col 20}{res}{space 2} .9327164{col 32}{space 2} 2.259416{col 43}{space 1}    0.41{col 52}{space 3}0.680{col 60}{space 4}-3.495657{col 73}{space 3}  5.36109
{txt}{space 15}23  {c |}{col 20}{res}{space 2} 5.907304{col 32}{space 2} 2.557005{col 43}{space 1}    2.31{col 52}{space 3}0.021{col 60}{space 4}  .895665{col 73}{space 3} 10.91894
{txt}{space 15}24  {c |}{col 20}{res}{space 2} 2.394216{col 32}{space 2} 2.221259{col 43}{space 1}    1.08{col 52}{space 3}0.281{col 60}{space 4}-1.959371{col 73}{space 3} 6.747803
{txt}{space 15}25  {c |}{col 20}{res}{space 2}  4.65579{col 32}{space 2} 4.039511{col 43}{space 1}    1.15{col 52}{space 3}0.249{col 60}{space 4}-3.261505{col 73}{space 3} 12.57309
{txt}{space 15}31  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}32  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}33  {c |}{col 20}{res}{space 2}-1.958933{col 32}{space 2} 2.496855{col 43}{space 1}   -0.78{col 52}{space 3}0.433{col 60}{space 4}-6.852679{col 73}{space 3} 2.934812
{txt}{space 15}34  {c |}{col 20}{res}{space 2} 1.651758{col 32}{space 2} 2.209807{col 43}{space 1}    0.75{col 52}{space 3}0.455{col 60}{space 4}-2.679385{col 73}{space 3}   5.9829
{txt}{space 15}35  {c |}{col 20}{res}{space 2} 1.023965{col 32}{space 2} 3.094264{col 43}{space 1}    0.33{col 52}{space 3}0.741{col 60}{space 4} -5.04068{col 73}{space 3}  7.08861
{txt}{space 15}36  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}37  {c |}{col 20}{res}{space 2} 5.113143{col 32}{space 2} 3.527364{col 43}{space 1}    1.45{col 52}{space 3}0.147{col 60}{space 4}-1.800362{col 73}{space 3} 12.02665
{txt}{space 15}40  {c |}{col 20}{res}{space 2}-2.548915{col 32}{space 2} 2.200559{col 43}{space 1}   -1.16{col 52}{space 3}0.247{col 60}{space 4}-6.861931{col 73}{space 3} 1.764102
{txt}{space 15}41  {c |}{col 20}{res}{space 2}-1.043481{col 32}{space 2} 2.480668{col 43}{space 1}   -0.42{col 52}{space 3}0.674{col 60}{space 4}-5.905501{col 73}{space 3} 3.818539
{txt}{space 15}42  {c |}{col 20}{res}{space 2} -2.31822{col 32}{space 2} 2.426375{col 43}{space 1}   -0.96{col 52}{space 3}0.339{col 60}{space 4}-7.073827{col 73}{space 3} 2.437387
{txt}{space 15}43  {c |}{col 20}{res}{space 2}-2.619531{col 32}{space 2} 2.079875{col 43}{space 1}   -1.26{col 52}{space 3}0.208{col 60}{space 4}-6.696012{col 73}{space 3}  1.45695
{txt}{space 15}44  {c |}{col 20}{res}{space 2}-.7503888{col 32}{space 2}  2.29597{col 43}{space 1}   -0.33{col 52}{space 3}0.744{col 60}{space 4}-5.250407{col 73}{space 3}  3.74963
{txt}{space 15}45  {c |}{col 20}{res}{space 2} 6.584074{col 32}{space 2} 2.957113{col 43}{space 1}    2.23{col 52}{space 3}0.026{col 60}{space 4} .7882387{col 73}{space 3} 12.37991
{txt}{space 15}46  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}47  {c |}{col 20}{res}{space 2}-1.566453{col 32}{space 2} 2.217348{col 43}{space 1}   -0.71{col 52}{space 3}0.480{col 60}{space 4}-5.912374{col 73}{space 3} 2.779469
{txt}{space 15}48  {c |}{col 20}{res}{space 2}-3.416255{col 32}{space 2} 2.468556{col 43}{space 1}   -1.38{col 52}{space 3}0.166{col 60}{space 4}-8.254536{col 73}{space 3} 1.422025
{txt}{space 15}49  {c |}{col 20}{res}{space 2} .2896205{col 32}{space 2} 2.236893{col 43}{space 1}    0.13{col 52}{space 3}0.897{col 60}{space 4}-4.094609{col 73}{space 3}  4.67385
{txt}{space 15}51  {c |}{col 20}{res}{space 2}-.9340375{col 32}{space 2} 2.497694{col 43}{space 1}   -0.37{col 52}{space 3}0.708{col 60}{space 4}-5.829429{col 73}{space 3} 3.961354
{txt}{space 15}52  {c |}{col 20}{res}{space 2}-2.786014{col 32}{space 2}  2.60418{col 43}{space 1}   -1.07{col 52}{space 3}0.285{col 60}{space 4}-7.890114{col 73}{space 3} 2.318086
{txt}{space 15}53  {c |}{col 20}{res}{space 2}  -3.9401{col 32}{space 2} 2.440962{col 43}{space 1}   -1.61{col 52}{space 3}0.106{col 60}{space 4}-8.724297{col 73}{space 3} .8440973
{txt}{space 15}54  {c |}{col 20}{res}{space 2} .5440603{col 32}{space 2} 2.192193{col 43}{space 1}    0.25{col 52}{space 3}0.804{col 60}{space 4}-3.752559{col 73}{space 3}  4.84068
{txt}{space 15}56  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}61  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}62  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}63  {c |}{col 20}{res}{space 2} 1.426977{col 32}{space 2} 2.661971{col 43}{space 1}    0.54{col 52}{space 3}0.592{col 60}{space 4} -3.79039{col 73}{space 3} 6.644344
{txt}{space 15}64  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}65  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}66  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}67  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}68  {c |}{col 20}{res}{space 2}-1.551126{col 32}{space 2} 2.730655{col 43}{space 1}   -0.57{col 52}{space 3}0.570{col 60}{space 4}-6.903112{col 73}{space 3}  3.80086
{txt}{space 15}71  {c |}{col 20}{res}{space 2}-.7074367{col 32}{space 2} 2.035995{col 43}{space 1}   -0.35{col 52}{space 3}0.728{col 60}{space 4}-4.697913{col 73}{space 3}  3.28304
{txt}{space 15}72  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}73  {c |}{col 20}{res}{space 2} 1.402542{col 32}{space 2} 2.602522{col 43}{space 1}    0.54{col 52}{space 3}0.590{col 60}{space 4}-3.698308{col 73}{space 3} 6.503391
{txt}{space 15}81  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}82  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  .512317{col 32}{space 2} 2.444215{col 43}{space 1}    0.21{col 52}{space 3}0.834{col 60}{space 4}-4.278256{col 73}{space 3}  5.30289
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_instate]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_instate]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_instate]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_instate]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_instate]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_instate]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_instate]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}    7.52
{txt}{col 10}Prob > chi2 =  {res}  0.3768
{txt}
{com}. 
. 
. *BORN IN-REGION (Bottom rows of Table 2)
. 
. egen Rep_region_group=group(RepRegion)
{txt}
{com}. egen Birth_region_group=group(BirthRegion)
{txt}
{com}. 
. *All members - Column 1
. logit born_inregion AgeInteger Female Black Hispanic dpres i.Birth_region_group i.Rep_region_group if congress<116

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 10 obs not used

note: 3.Birth_region_group != 0 predicts failure perfectly
      3.Birth_region_group dropped and 1 obs not used

note: 4.Birth_region_group != 0 predicts failure perfectly
      4.Birth_region_group dropped and 2 obs not used

note: 6.Birth_region_group != 0 predicts failure perfectly
      6.Birth_region_group dropped and 1 obs not used

note: 8.Birth_region_group != 0 predicts failure perfectly
      8.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 6 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 4 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 4 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-549.20564}  
Iteration 1:{space 3}log likelihood = {res:-432.06556}  
Iteration 2:{space 3}log likelihood = {res:-428.63167}  
Iteration 3:{space 3}log likelihood = {res:-428.62469}  
Iteration 4:{space 3}log likelihood = {res:-428.62469}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       959
{txt}{col 49}LR chi2({res}21{txt}){col 67}= {res}    241.16
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-428.62469{txt}{col 49}Pseudo R2{col 67}= {res}    0.2196

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0148791{col 32}{space 2} .0091358{col 43}{space 1}   -1.63{col 52}{space 3}0.103{col 60}{space 4}-.0327849{col 73}{space 3} .0030268
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.4214643{col 32}{space 2} .2351303{col 43}{space 1}   -1.79{col 52}{space 3}0.073{col 60}{space 4}-.8823112{col 73}{space 3} .0393825
{txt}{space 13}Black {c |}{col 20}{res}{space 2}-.2613402{col 32}{space 2} .3895069{col 43}{space 1}   -0.67{col 52}{space 3}0.502{col 60}{space 4} -1.02476{col 73}{space 3} .5020792
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .2545045{col 32}{space 2} .4632858{col 43}{space 1}    0.55{col 52}{space 3}0.583{col 60}{space 4}-.6535189{col 73}{space 3} 1.162528
{txt}{space 13}dpres {c |}{col 20}{res}{space 2} -.002111{col 32}{space 2} .0084729{col 43}{space 1}   -0.25{col 52}{space 3}0.803{col 60}{space 4}-.0187176{col 73}{space 3} .0144956
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2} .2742183{col 32}{space 2} .5244963{col 43}{space 1}    0.52{col 52}{space 3}0.601{col 60}{space 4}-.7537755{col 73}{space 3} 1.302212
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2} .3102025{col 32}{space 2} .4964535{col 43}{space 1}    0.62{col 52}{space 3}0.532{col 60}{space 4}-.6628285{col 73}{space 3} 1.283234
{txt}{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}7  {c |}{col 20}{res}{space 2} 1.006422{col 32}{space 2} 1.443321{col 43}{space 1}    0.70{col 52}{space 3}0.486{col 60}{space 4}-1.822436{col 73}{space 3}  3.83528
{txt}{space 16}8  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.2505865{col 32}{space 2} .5010264{col 43}{space 1}   -0.50{col 52}{space 3}0.617{col 60}{space 4} -1.23258{col 73}{space 3} .7314073
{txt}{space 15}10  {c |}{col 20}{res}{space 2} 3.895715{col 32}{space 2} .7125556{col 43}{space 1}    5.47{col 52}{space 3}0.000{col 60}{space 4} 2.499132{col 73}{space 3} 5.292298
{txt}{space 15}11  {c |}{col 20}{res}{space 2} .3084121{col 32}{space 2} .5914102{col 43}{space 1}    0.52{col 52}{space 3}0.602{col 60}{space 4}-.8507306{col 73}{space 3} 1.467555
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 3.042039{col 32}{space 2} .5703472{col 43}{space 1}    5.33{col 52}{space 3}0.000{col 60}{space 4} 1.924179{col 73}{space 3} 4.159899
{txt}{space 15}14  {c |}{col 20}{res}{space 2}  3.08653{col 32}{space 2} .4878608{col 43}{space 1}    6.33{col 52}{space 3}0.000{col 60}{space 4}  2.13034{col 73}{space 3} 4.042719
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2} 1.234949{col 32}{space 2} .5187336{col 43}{space 1}    2.38{col 52}{space 3}0.017{col 60}{space 4} .2182495{col 73}{space 3} 2.251648
{txt}{space 16}3  {c |}{col 20}{res}{space 2}-.8354486{col 32}{space 2} 1.413964{col 43}{space 1}   -0.59{col 52}{space 3}0.555{col 60}{space 4}-3.606766{col 73}{space 3} 1.935869
{txt}{space 16}4  {c |}{col 20}{res}{space 2} 1.531627{col 32}{space 2} .4875905{col 43}{space 1}    3.14{col 52}{space 3}0.002{col 60}{space 4}  .575967{col 73}{space 3} 2.487287
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-2.860157{col 32}{space 2} .6259817{col 43}{space 1}   -4.57{col 52}{space 3}0.000{col 60}{space 4}-4.087058{col 73}{space 3}-1.633255
{txt}{space 16}6  {c |}{col 20}{res}{space 2} .3161485{col 32}{space 2} .5973869{col 43}{space 1}    0.53{col 52}{space 3}0.597{col 60}{space 4}-.8547084{col 73}{space 3} 1.487005
{txt}{space 16}7  {c |}{col 20}{res}{space 2}-2.017892{col 32}{space 2} .5460441{col 43}{space 1}   -3.70{col 52}{space 3}0.000{col 60}{space 4}-3.088118{col 73}{space 3}-.9476648
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-1.437981{col 32}{space 2} .4263956{col 43}{space 1}   -3.37{col 52}{space 3}0.001{col 60}{space 4}-2.273701{col 73}{space 3}-.6022606
{txt}{space 16}9  {c |}{col 20}{res}{space 2} 1.008238{col 32}{space 2} .5802803{col 43}{space 1}    1.74{col 52}{space 3}0.082{col 60}{space 4}-.1290904{col 73}{space 3} 2.145567
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}  1.27611{col 32}{space 2} .7781257{col 43}{space 1}    1.64{col 52}{space 3}0.101{col 60}{space 4}-.2489879{col 73}{space 3} 2.801209
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    9.34
{txt}{col 10}Prob > chi2 =  {res}  0.0964
{txt}
{com}. 
. *All members - Column 2
. logit born_inregion AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.Birth_region_group i.Rep_region_group if congress<116

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 10 obs not used

note: 3.Birth_region_group != 0 predicts failure perfectly
      3.Birth_region_group dropped and 1 obs not used

note: 4.Birth_region_group != 0 predicts failure perfectly
      4.Birth_region_group dropped and 2 obs not used

note: 6.Birth_region_group != 0 predicts failure perfectly
      6.Birth_region_group dropped and 1 obs not used

note: 8.Birth_region_group != 0 predicts failure perfectly
      8.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 6 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 4 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 4 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-548.90483}  
Iteration 1:{space 3}log likelihood = {res: -430.7298}  
Iteration 2:{space 3}log likelihood = {res:-427.15368}  
Iteration 3:{space 3}log likelihood = {res:-427.13053}  
Iteration 4:{space 3}log likelihood = {res:-427.13053}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       958
{txt}{col 49}LR chi2({res}23{txt}){col 67}= {res}    243.55
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-427.13053{txt}{col 49}Pseudo R2{col 67}= {res}    0.2218

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0201371{col 32}{space 2} .0102624{col 43}{space 1}   -1.96{col 52}{space 3}0.050{col 60}{space 4}-.0402511{col 73}{space 3}-.0000232
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.4274808{col 32}{space 2} .2415443{col 43}{space 1}   -1.77{col 52}{space 3}0.077{col 60}{space 4} -.900899{col 73}{space 3} .0459374
{txt}{space 13}Black {c |}{col 20}{res}{space 2}-.2761859{col 32}{space 2} .3932696{col 43}{space 1}   -0.70{col 52}{space 3}0.483{col 60}{space 4} -1.04698{col 73}{space 3} .4946084
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .1998164{col 32}{space 2} .4683647{col 43}{space 1}    0.43{col 52}{space 3}0.670{col 60}{space 4}-.7181615{col 73}{space 3} 1.117794
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0102961{col 32}{space 2}  .010262{col 43}{space 1}   -1.00{col 52}{space 3}0.316{col 60}{space 4}-.0304092{col 73}{space 3} .0098169
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2}-.4090213{col 32}{space 2} .3102388{col 43}{space 1}   -1.32{col 52}{space 3}0.187{col 60}{space 4}-1.017078{col 73}{space 3} .1990356
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2} .0232924{col 32}{space 2} .0295432{col 43}{space 1}    0.79{col 52}{space 3}0.430{col 60}{space 4}-.0346112{col 73}{space 3} .0811961
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2} .2263932{col 32}{space 2} .5245072{col 43}{space 1}    0.43{col 52}{space 3}0.666{col 60}{space 4} -.801622{col 73}{space 3} 1.254409
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2} .3352428{col 32}{space 2} .4940884{col 43}{space 1}    0.68{col 52}{space 3}0.497{col 60}{space 4}-.6331526{col 73}{space 3} 1.303638
{txt}{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}7  {c |}{col 20}{res}{space 2} 1.081285{col 32}{space 2} 1.440782{col 43}{space 1}    0.75{col 52}{space 3}0.453{col 60}{space 4}-1.742596{col 73}{space 3} 3.905166
{txt}{space 16}8  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.2651938{col 32}{space 2} .4987093{col 43}{space 1}   -0.53{col 52}{space 3}0.595{col 60}{space 4}-1.242646{col 73}{space 3} .7122585
{txt}{space 15}10  {c |}{col 20}{res}{space 2} 3.855673{col 32}{space 2} .7133241{col 43}{space 1}    5.41{col 52}{space 3}0.000{col 60}{space 4} 2.457584{col 73}{space 3} 5.253763
{txt}{space 15}11  {c |}{col 20}{res}{space 2} .2854704{col 32}{space 2} .5903756{col 43}{space 1}    0.48{col 52}{space 3}0.629{col 60}{space 4}-.8716446{col 73}{space 3} 1.442585
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 3.052768{col 32}{space 2} .5708518{col 43}{space 1}    5.35{col 52}{space 3}0.000{col 60}{space 4} 1.933919{col 73}{space 3} 4.171617
{txt}{space 15}14  {c |}{col 20}{res}{space 2} 3.050491{col 32}{space 2} .4867059{col 43}{space 1}    6.27{col 52}{space 3}0.000{col 60}{space 4} 2.096565{col 73}{space 3} 4.004417
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2} 1.189841{col 32}{space 2} .5196598{col 43}{space 1}    2.29{col 52}{space 3}0.022{col 60}{space 4} .1713263{col 73}{space 3} 2.208355
{txt}{space 16}3  {c |}{col 20}{res}{space 2}-.9944963{col 32}{space 2}  1.40999{col 43}{space 1}   -0.71{col 52}{space 3}0.481{col 60}{space 4}-3.758026{col 73}{space 3} 1.769034
{txt}{space 16}4  {c |}{col 20}{res}{space 2} 1.516969{col 32}{space 2} .4886229{col 43}{space 1}    3.10{col 52}{space 3}0.002{col 60}{space 4} .5592856{col 73}{space 3} 2.474652
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-2.805753{col 32}{space 2} .6268877{col 43}{space 1}   -4.48{col 52}{space 3}0.000{col 60}{space 4}-4.034431{col 73}{space 3}-1.577076
{txt}{space 16}6  {c |}{col 20}{res}{space 2} .2312986{col 32}{space 2} .6004662{col 43}{space 1}    0.39{col 52}{space 3}0.700{col 60}{space 4}-.9455935{col 73}{space 3} 1.408191
{txt}{space 16}7  {c |}{col 20}{res}{space 2} -2.05636{col 32}{space 2} .5461484{col 43}{space 1}   -3.77{col 52}{space 3}0.000{col 60}{space 4}-3.126791{col 73}{space 3}-.9859287
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-1.412895{col 32}{space 2} .4277685{col 43}{space 1}   -3.30{col 52}{space 3}0.001{col 60}{space 4}-2.251305{col 73}{space 3}-.5744838
{txt}{space 16}9  {c |}{col 20}{res}{space 2} .9816823{col 32}{space 2} .5780373{col 43}{space 1}    1.70{col 52}{space 3}0.089{col 60}{space 4}  -.15125{col 73}{space 3} 2.114614
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 1.953372{col 32}{space 2} .8883928{col 43}{space 1}    2.20{col 52}{space 3}0.028{col 60}{space 4} .2121539{col 73}{space 3}  3.69459
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_inregion]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_inregion]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}   11.96
{txt}{col 10}Prob > chi2 =  {res}  0.1018
{txt}
{com}. 
. *Democrats - Column 3
. logit born_inregion AgeInteger Female Black Hispanic dpres i.Birth_region_group i.Rep_region_group if congress<116 & party_code==100

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 9 obs not used

note: 3.Birth_region_group != 0 predicts failure perfectly
      3.Birth_region_group dropped and 1 obs not used

note: 4.Birth_region_group != 0 predicts failure perfectly
      4.Birth_region_group dropped and 2 obs not used

note: 6.Birth_region_group != 0 predicts failure perfectly
      6.Birth_region_group dropped and 1 obs not used

note: 8.Birth_region_group != 0 predicts failure perfectly
      8.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 5 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 2 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 1 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-240.01267}  
Iteration 1:{space 3}log likelihood = {res:-173.97353}  
Iteration 2:{space 3}log likelihood = {res:-172.39694}  
Iteration 3:{space 3}log likelihood = {res:-172.39201}  
Iteration 4:{space 3}log likelihood = {res:-172.39201}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       422
{txt}{col 49}LR chi2({res}21{txt}){col 67}= {res}    135.24
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-172.39201{txt}{col 49}Pseudo R2{col 67}= {res}    0.2817

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0247707{col 32}{space 2} .0148747{col 43}{space 1}   -1.67{col 52}{space 3}0.096{col 60}{space 4}-.0539246{col 73}{space 3} .0043831
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.2640174{col 32}{space 2}  .341854{col 43}{space 1}   -0.77{col 52}{space 3}0.440{col 60}{space 4} -.934039{col 73}{space 3} .4060042
{txt}{space 13}Black {c |}{col 20}{res}{space 2} .1233022{col 32}{space 2} .5029286{col 43}{space 1}    0.25{col 52}{space 3}0.806{col 60}{space 4}-.8624199{col 73}{space 3} 1.109024
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .7158386{col 32}{space 2} .6103168{col 43}{space 1}    1.17{col 52}{space 3}0.241{col 60}{space 4}-.4803603{col 73}{space 3} 1.912037
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0181446{col 32}{space 2} .0148689{col 43}{space 1}   -1.22{col 52}{space 3}0.222{col 60}{space 4}-.0472871{col 73}{space 3} .0109979
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2}-1.596258{col 32}{space 2} 1.326012{col 43}{space 1}   -1.20{col 52}{space 3}0.229{col 60}{space 4}-4.195193{col 73}{space 3} 1.002677
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2} 1.764598{col 32}{space 2} 1.295147{col 43}{space 1}    1.36{col 52}{space 3}0.173{col 60}{space 4}-.7738427{col 73}{space 3} 4.303039
{txt}{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}7  {c |}{col 20}{res}{space 2} -2.74555{col 32}{space 2} 1.961496{col 43}{space 1}   -1.40{col 52}{space 3}0.162{col 60}{space 4}-6.590011{col 73}{space 3} 1.098911
{txt}{space 16}8  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.8980801{col 32}{space 2} 1.211249{col 43}{space 1}   -0.74{col 52}{space 3}0.458{col 60}{space 4}-3.272084{col 73}{space 3} 1.475924
{txt}{space 15}10  {c |}{col 20}{res}{space 2} 1.821112{col 32}{space 2} 1.412573{col 43}{space 1}    1.29{col 52}{space 3}0.197{col 60}{space 4}-.9474812{col 73}{space 3} 4.589704
{txt}{space 15}11  {c |}{col 20}{res}{space 2} 2.067214{col 32}{space 2} 1.264627{col 43}{space 1}    1.63{col 52}{space 3}0.102{col 60}{space 4}-.4114086{col 73}{space 3} 4.545836
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 4.923998{col 32}{space 2} 1.327244{col 43}{space 1}    3.71{col 52}{space 3}0.000{col 60}{space 4} 2.322648{col 73}{space 3} 7.525348
{txt}{space 15}14  {c |}{col 20}{res}{space 2} 1.867808{col 32}{space 2} 1.222737{col 43}{space 1}    1.53{col 52}{space 3}0.127{col 60}{space 4}-.5287126{col 73}{space 3} 4.264328
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2} -2.05569{col 32}{space 2} .9652658{col 43}{space 1}   -2.13{col 52}{space 3}0.033{col 60}{space 4}-3.947576{col 73}{space 3}-.1638033
{txt}{space 16}3  {c |}{col 20}{res}{space 2} 2.035604{col 32}{space 2} 1.967031{col 43}{space 1}    1.03{col 52}{space 3}0.301{col 60}{space 4}-1.819705{col 73}{space 3} 5.890914
{txt}{space 16}4  {c |}{col 20}{res}{space 2} .1786827{col 32}{space 2} .7532595{col 43}{space 1}    0.24{col 52}{space 3}0.812{col 60}{space 4}-1.297679{col 73}{space 3} 1.655044
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-3.526542{col 32}{space 2} 1.108802{col 43}{space 1}   -3.18{col 52}{space 3}0.001{col 60}{space 4}-5.699754{col 73}{space 3}-1.353331
{txt}{space 16}6  {c |}{col 20}{res}{space 2}-2.624069{col 32}{space 2} 1.038816{col 43}{space 1}   -2.53{col 52}{space 3}0.012{col 60}{space 4} -4.66011{col 73}{space 3}-.5880277
{txt}{space 16}7  {c |}{col 20}{res}{space 2}-5.473217{col 32}{space 2}  .997264{col 43}{space 1}   -5.49{col 52}{space 3}0.000{col 60}{space 4}-7.427818{col 73}{space 3}-3.518615
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-2.642307{col 32}{space 2} .8173965{col 43}{space 1}   -3.23{col 52}{space 3}0.001{col 60}{space 4}-4.244374{col 73}{space 3}-1.040239
{txt}{space 16}9  {c |}{col 20}{res}{space 2}-.7740449{col 32}{space 2} 1.481272{col 43}{space 1}   -0.52{col 52}{space 3}0.601{col 60}{space 4}-3.677284{col 73}{space 3} 2.129194
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 4.819188{col 32}{space 2} 1.739082{col 43}{space 1}    2.77{col 52}{space 3}0.006{col 60}{space 4}  1.41065{col 73}{space 3} 8.227725
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    7.27
{txt}{col 10}Prob > chi2 =  {res}  0.2011
{txt}
{com}. 
. *Democrats - Column 4
. logit born_inregion AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.Birth_region_group i.Rep_region_group if congress<116 & party_code==100

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 9 obs not used

note: 3.Birth_region_group != 0 predicts failure perfectly
      3.Birth_region_group dropped and 1 obs not used

note: 4.Birth_region_group != 0 predicts failure perfectly
      4.Birth_region_group dropped and 2 obs not used

note: 6.Birth_region_group != 0 predicts failure perfectly
      6.Birth_region_group dropped and 1 obs not used

note: 8.Birth_region_group != 0 predicts failure perfectly
      8.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 5 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 2 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 1 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-240.01267}  
Iteration 1:{space 3}log likelihood = {res:-173.37928}  
Iteration 2:{space 3}log likelihood = {res:-171.71019}  
Iteration 3:{space 3}log likelihood = {res:-171.70493}  
Iteration 4:{space 3}log likelihood = {res:-171.70493}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       422
{txt}{col 49}LR chi2({res}23{txt}){col 67}= {res}    136.62
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-171.70493{txt}{col 49}Pseudo R2{col 67}= {res}    0.2846

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0270583{col 32}{space 2} .0164623{col 43}{space 1}   -1.64{col 52}{space 3}0.100{col 60}{space 4}-.0593238{col 73}{space 3} .0052072
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.3058622{col 32}{space 2} .3525199{col 43}{space 1}   -0.87{col 52}{space 3}0.386{col 60}{space 4}-.9967885{col 73}{space 3}  .385064
{txt}{space 13}Black {c |}{col 20}{res}{space 2} .0122159{col 32}{space 2} .5183286{col 43}{space 1}    0.02{col 52}{space 3}0.981{col 60}{space 4} -1.00369{col 73}{space 3} 1.028121
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .6226247{col 32}{space 2}  .617197{col 43}{space 1}    1.01{col 52}{space 3}0.313{col 60}{space 4}-.5870592{col 73}{space 3} 1.832309
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0283578{col 32}{space 2}   .01737{col 43}{space 1}   -1.63{col 52}{space 3}0.103{col 60}{space 4}-.0624023{col 73}{space 3} .0056868
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2}-1.759625{col 32}{space 2} 1.510076{col 43}{space 1}   -1.17{col 52}{space 3}0.244{col 60}{space 4}-4.719319{col 73}{space 3} 1.200069
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2}-.0089909{col 32}{space 2} .0424056{col 43}{space 1}   -0.21{col 52}{space 3}0.832{col 60}{space 4}-.0921045{col 73}{space 3} .0741226
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2}-1.592184{col 32}{space 2} 1.314397{col 43}{space 1}   -1.21{col 52}{space 3}0.226{col 60}{space 4}-4.168356{col 73}{space 3} .9839873
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}5  {c |}{col 20}{res}{space 2} 1.738554{col 32}{space 2} 1.286517{col 43}{space 1}    1.35{col 52}{space 3}0.177{col 60}{space 4}-.7829726{col 73}{space 3} 4.260081
{txt}{space 16}6  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}7  {c |}{col 20}{res}{space 2}-2.641138{col 32}{space 2} 1.961871{col 43}{space 1}   -1.35{col 52}{space 3}0.178{col 60}{space 4}-6.486334{col 73}{space 3} 1.204059
{txt}{space 16}8  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.8777274{col 32}{space 2} 1.198371{col 43}{space 1}   -0.73{col 52}{space 3}0.464{col 60}{space 4}-3.226491{col 73}{space 3} 1.471036
{txt}{space 15}10  {c |}{col 20}{res}{space 2}  1.79798{col 32}{space 2}   1.4033{col 43}{space 1}    1.28{col 52}{space 3}0.200{col 60}{space 4}-.9524378{col 73}{space 3} 4.548398
{txt}{space 15}11  {c |}{col 20}{res}{space 2} 2.059363{col 32}{space 2} 1.254959{col 43}{space 1}    1.64{col 52}{space 3}0.101{col 60}{space 4}-.4003107{col 73}{space 3} 4.519036
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 4.962279{col 32}{space 2} 1.321931{col 43}{space 1}    3.75{col 52}{space 3}0.000{col 60}{space 4} 2.371341{col 73}{space 3} 7.553217
{txt}{space 15}14  {c |}{col 20}{res}{space 2} 1.917806{col 32}{space 2} 1.215356{col 43}{space 1}    1.58{col 52}{space 3}0.115{col 60}{space 4}-.4642486{col 73}{space 3} 4.299861
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2}-2.085982{col 32}{space 2}   .96725{col 43}{space 1}   -2.16{col 52}{space 3}0.031{col 60}{space 4}-3.981757{col 73}{space 3}-.1902071
{txt}{space 16}3  {c |}{col 20}{res}{space 2} 1.913502{col 32}{space 2} 1.975137{col 43}{space 1}    0.97{col 52}{space 3}0.333{col 60}{space 4}-1.957695{col 73}{space 3}   5.7847
{txt}{space 16}4  {c |}{col 20}{res}{space 2} .1265991{col 32}{space 2} .7527353{col 43}{space 1}    0.17{col 52}{space 3}0.866{col 60}{space 4}-1.348735{col 73}{space 3} 1.601933
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-3.508886{col 32}{space 2} 1.111741{col 43}{space 1}   -3.16{col 52}{space 3}0.002{col 60}{space 4}-5.687858{col 73}{space 3}-1.329915
{txt}{space 16}6  {c |}{col 20}{res}{space 2}-2.763151{col 32}{space 2} 1.044715{col 43}{space 1}   -2.64{col 52}{space 3}0.008{col 60}{space 4}-4.810755{col 73}{space 3}-.7155481
{txt}{space 16}7  {c |}{col 20}{res}{space 2}-5.606725{col 32}{space 2} 1.006556{col 43}{space 1}   -5.57{col 52}{space 3}0.000{col 60}{space 4}-7.579539{col 73}{space 3} -3.63391
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-2.670697{col 32}{space 2} .8200373{col 43}{space 1}   -3.26{col 52}{space 3}0.001{col 60}{space 4}-4.277941{col 73}{space 3}-1.063454
{txt}{space 16}9  {c |}{col 20}{res}{space 2}-.8613171{col 32}{space 2} 1.474333{col 43}{space 1}   -0.58{col 52}{space 3}0.559{col 60}{space 4}-3.750957{col 73}{space 3} 2.028322
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2} 5.055248{col 32}{space 2} 1.759065{col 43}{space 1}    2.87{col 52}{space 3}0.004{col 60}{space 4} 1.607544{col 73}{space 3} 8.502953
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_inregion]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_inregion]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}    8.62
{txt}{col 10}Prob > chi2 =  {res}  0.2811
{txt}
{com}. 
. *Republicans - Column 5
. logit born_inregion AgeInteger Female Black Hispanic dpres i.Birth_region_group i.Rep_region_group if congress<116 & party_code==200

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 1 obs not used

note: 7.Birth_region_group != 0 predicts failure perfectly
      7.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 1 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 2 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 3 obs not used

note: 3.Rep_region_group != 0 predicts failure perfectly
      3.Rep_region_group dropped and 2 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res: -303.7745}  
Iteration 1:{space 3}log likelihood = {res:-201.30125}  
Iteration 2:{space 3}log likelihood = {res:-198.14594}  
Iteration 3:{space 3}log likelihood = {res:-198.09218}  
Iteration 4:{space 3}log likelihood = {res:-198.09184}  
Iteration 5:{space 3}log likelihood = {res:-198.09184}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       533
{txt}{col 49}LR chi2({res}19{txt}){col 67}= {res}    211.37
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-198.09184{txt}{col 49}Pseudo R2{col 67}= {res}    0.3479

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0017583{col 32}{space 2} .0140288{col 43}{space 1}   -0.13{col 52}{space 3}0.900{col 60}{space 4}-.0292542{col 73}{space 3} .0257376
{txt}{space 12}Female {c |}{col 20}{res}{space 2} -.326094{col 32}{space 2} .4268966{col 43}{space 1}   -0.76{col 52}{space 3}0.445{col 60}{space 4}-1.162796{col 73}{space 3} .5106079
{txt}{space 13}Black {c |}{col 20}{res}{space 2} 2.252177{col 32}{space 2} 2.716958{col 43}{space 1}    0.83{col 52}{space 3}0.407{col 60}{space 4}-3.072962{col 73}{space 3} 7.577316
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2}-.0013777{col 32}{space 2} 1.036623{col 43}{space 1}   -0.00{col 52}{space 3}0.999{col 60}{space 4}-2.033121{col 73}{space 3} 2.030366
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0064948{col 32}{space 2} .0161892{col 43}{space 1}   -0.40{col 52}{space 3}0.688{col 60}{space 4}-.0382251{col 73}{space 3} .0252354
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2} 1.453267{col 32}{space 2} .6852434{col 43}{space 1}    2.12{col 52}{space 3}0.034{col 60}{space 4}  .110215{col 73}{space 3}  2.79632
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-.6630183{col 32}{space 2} .6346014{col 43}{space 1}   -1.04{col 52}{space 3}0.296{col 60}{space 4}-1.906814{col 73}{space 3} .5807776
{txt}{space 16}7  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.6841529{col 32}{space 2} .6958013{col 43}{space 1}   -0.98{col 52}{space 3}0.325{col 60}{space 4}-2.047898{col 73}{space 3} .6795926
{txt}{space 15}10  {c |}{col 20}{res}{space 2} 6.373926{col 32}{space 2} 1.247887{col 43}{space 1}    5.11{col 52}{space 3}0.000{col 60}{space 4} 3.928113{col 73}{space 3} 8.819739
{txt}{space 15}11  {c |}{col 20}{res}{space 2}-2.041915{col 32}{space 2} .9555289{col 43}{space 1}   -2.14{col 52}{space 3}0.033{col 60}{space 4}-3.914717{col 73}{space 3}-.1691125
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 1.710504{col 32}{space 2} .7886685{col 43}{space 1}    2.17{col 52}{space 3}0.030{col 60}{space 4} .1647422{col 73}{space 3} 3.256266
{txt}{space 15}14  {c |}{col 20}{res}{space 2} 3.872558{col 32}{space 2} .6306087{col 43}{space 1}    6.14{col 52}{space 3}0.000{col 60}{space 4} 2.636588{col 73}{space 3} 5.108528
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2} 3.350216{col 32}{space 2} .7641943{col 43}{space 1}    4.38{col 52}{space 3}0.000{col 60}{space 4} 1.852423{col 73}{space 3} 4.848009
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2}  3.33157{col 32}{space 2} .8080835{col 43}{space 1}    4.12{col 52}{space 3}0.000{col 60}{space 4} 1.747755{col 73}{space 3} 4.915385
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-3.128894{col 32}{space 2}  1.05441{col 43}{space 1}   -2.97{col 52}{space 3}0.003{col 60}{space 4}  -5.1955{col 73}{space 3}-1.062288
{txt}{space 16}6  {c |}{col 20}{res}{space 2} 2.482773{col 32}{space 2} 1.080197{col 43}{space 1}    2.30{col 52}{space 3}0.022{col 60}{space 4} .3656257{col 73}{space 3}  4.59992
{txt}{space 16}7  {c |}{col 20}{res}{space 2} .8370712{col 32}{space 2}  .893871{col 43}{space 1}    0.94{col 52}{space 3}0.349{col 60}{space 4}-.9148839{col 73}{space 3} 2.589026
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-.7688521{col 32}{space 2} .5878715{col 43}{space 1}   -1.31{col 52}{space 3}0.191{col 60}{space 4}-1.921059{col 73}{space 3} .3833549
{txt}{space 16}9  {c |}{col 20}{res}{space 2} 1.987992{col 32}{space 2}  .729974{col 43}{space 1}    2.72{col 52}{space 3}0.006{col 60}{space 4} .5572689{col 73}{space 3} 3.418714
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-.3367785{col 32}{space 2}  1.14974{col 43}{space 1}   -0.29{col 52}{space 3}0.770{col 60}{space 4}-2.590227{col 73}{space 3}  1.91667
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}

{txt}{col 12}chi2(  5) ={res}    1.41
{txt}{col 10}Prob > chi2 =  {res}  0.9237
{txt}
{com}. 
. *Republicans - Column 6
. logit born_inregion AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew i.Birth_region_group i.Rep_region_group if congress<116 & party_code==200

{txt}note: 1.Birth_region_group != 0 predicts failure perfectly
      1.Birth_region_group dropped and 1 obs not used

note: 7.Birth_region_group != 0 predicts failure perfectly
      7.Birth_region_group dropped and 1 obs not used

note: 12.Birth_region_group != 0 predicts failure perfectly
      12.Birth_region_group dropped and 1 obs not used

note: 15.Birth_region_group != 0 predicts failure perfectly
      15.Birth_region_group dropped and 2 obs not used

note: 17.Birth_region_group != 0 predicts failure perfectly
      17.Birth_region_group dropped and 3 obs not used

note: 3.Rep_region_group != 0 predicts failure perfectly
      3.Rep_region_group dropped and 2 obs not used

note: 16.Birth_region_group omitted because of collinearity
{res}{txt}Iteration 0:{space 3}log likelihood = {res:-303.47707}  
Iteration 1:{space 3}log likelihood = {res:-200.09814}  
Iteration 2:{space 3}log likelihood = {res:-196.67825}  
Iteration 3:{space 3}log likelihood = {res: -196.6217}  
Iteration 4:{space 3}log likelihood = {res:-196.62136}  
Iteration 5:{space 3}log likelihood = {res:-196.62136}  
{res}
{txt}Logistic regression{col 49}Number of obs{col 67}= {res}       532
{txt}{col 49}LR chi2({res}21{txt}){col 67}= {res}    213.71
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log likelihood = {res}-196.62136{txt}{col 49}Pseudo R2{col 67}= {res}    0.3521

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}     born_inregion{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      z{col 52}   P>|z|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}AgeInteger {c |}{col 20}{res}{space 2}-.0119226{col 32}{space 2} .0156906{col 43}{space 1}   -0.76{col 52}{space 3}0.447{col 60}{space 4}-.0426755{col 73}{space 3} .0188303
{txt}{space 12}Female {c |}{col 20}{res}{space 2}-.2693629{col 32}{space 2}  .434011{col 43}{space 1}   -0.62{col 52}{space 3}0.535{col 60}{space 4}-1.120009{col 73}{space 3}  .581283
{txt}{space 13}Black {c |}{col 20}{res}{space 2} 2.198888{col 32}{space 2} 2.711816{col 43}{space 1}    0.81{col 52}{space 3}0.417{col 60}{space 4}-3.116173{col 73}{space 3} 7.513949
{txt}{space 10}Hispanic {c |}{col 20}{res}{space 2} .0550991{col 32}{space 2}  1.04722{col 43}{space 1}    0.05{col 52}{space 3}0.958{col 60}{space 4}-1.997414{col 73}{space 3} 2.107613
{txt}{space 13}dpres {c |}{col 20}{res}{space 2}-.0076673{col 32}{space 2}  .016741{col 43}{space 1}   -0.46{col 52}{space 3}0.647{col 60}{space 4}-.0404791{col 73}{space 3} .0251445
{txt}{space 5}nominate_dim1 {c |}{col 20}{res}{space 2} .2972325{col 32}{space 2} 1.075722{col 43}{space 1}    0.28{col 52}{space 3}0.782{col 60}{space 4}-1.811143{col 73}{space 3} 2.405608
{txt}ChamSeniority_Stew {c |}{col 20}{res}{space 2} .0843732{col 32}{space 2} .0528056{col 43}{space 1}    1.60{col 52}{space 3}0.110{col 60}{space 4}-.0191239{col 73}{space 3} .1878702
{txt}{space 18} {c |}
Birth_region_group {c |}
{space 16}1  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}2  {c |}{col 20}{res}{space 2} 1.512311{col 32}{space 2} .6930388{col 43}{space 1}    2.18{col 52}{space 3}0.029{col 60}{space 4} .1539797{col 73}{space 3} 2.870642
{txt}{space 16}5  {c |}{col 20}{res}{space 2}-.5757105{col 32}{space 2} .6332869{col 43}{space 1}   -0.91{col 52}{space 3}0.363{col 60}{space 4} -1.81693{col 73}{space 3}  .665509
{txt}{space 16}7  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}9  {c |}{col 20}{res}{space 2}-.6102451{col 32}{space 2} .6906284{col 43}{space 1}   -0.88{col 52}{space 3}0.377{col 60}{space 4}-1.963852{col 73}{space 3} .7433616
{txt}{space 15}10  {c |}{col 20}{res}{space 2}  6.46411{col 32}{space 2} 1.253615{col 43}{space 1}    5.16{col 52}{space 3}0.000{col 60}{space 4}  4.00707{col 73}{space 3} 8.921151
{txt}{space 15}11  {c |}{col 20}{res}{space 2}-1.921155{col 32}{space 2} .9566771{col 43}{space 1}   -2.01{col 52}{space 3}0.045{col 60}{space 4}-3.796207{col 73}{space 3}-.0461021
{txt}{space 15}12  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}13  {c |}{col 20}{res}{space 2} 1.819389{col 32}{space 2} .7999122{col 43}{space 1}    2.27{col 52}{space 3}0.023{col 60}{space 4} .2515898{col 73}{space 3} 3.387188
{txt}{space 15}14  {c |}{col 20}{res}{space 2}  3.92096{col 32}{space 2} .6364723{col 43}{space 1}    6.16{col 52}{space 3}0.000{col 60}{space 4} 2.673497{col 73}{space 3} 5.168423
{txt}{space 15}15  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 15}16  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (omitted)
{space 15}17  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 18} {c |}
{space 2}Rep_region_group {c |}
{space 16}2  {c |}{col 20}{res}{space 2} 3.333085{col 32}{space 2} .7666019{col 43}{space 1}    4.35{col 52}{space 3}0.000{col 60}{space 4} 1.830572{col 73}{space 3} 4.835597
{txt}{space 16}3  {c |}{col 20}{res}{space 2}        0{col 32}{txt}  (empty)
{space 16}4  {c |}{col 20}{res}{space 2} 3.377732{col 32}{space 2} .8222061{col 43}{space 1}    4.11{col 52}{space 3}0.000{col 60}{space 4} 1.766237{col 73}{space 3} 4.989226
{txt}{space 16}5  {c |}{col 20}{res}{space 2} -3.14055{col 32}{space 2} 1.054957{col 43}{space 1}   -2.98{col 52}{space 3}0.003{col 60}{space 4}-5.208227{col 73}{space 3}-1.072873
{txt}{space 16}6  {c |}{col 20}{res}{space 2} 2.445173{col 32}{space 2} 1.085383{col 43}{space 1}    2.25{col 52}{space 3}0.024{col 60}{space 4} .3178609{col 73}{space 3} 4.572485
{txt}{space 16}7  {c |}{col 20}{res}{space 2} .7350996{col 32}{space 2} .9058732{col 43}{space 1}    0.81{col 52}{space 3}0.417{col 60}{space 4}-1.040379{col 73}{space 3} 2.510578
{txt}{space 16}8  {c |}{col 20}{res}{space 2}-.7586209{col 32}{space 2} .5948398{col 43}{space 1}   -1.28{col 52}{space 3}0.202{col 60}{space 4}-1.924486{col 73}{space 3} .4072437
{txt}{space 16}9  {c |}{col 20}{res}{space 2} 2.072924{col 32}{space 2} .7394607{col 43}{space 1}    2.80{col 52}{space 3}0.005{col 60}{space 4} .6236077{col 73}{space 3}  3.52224
{txt}{space 18} {c |}
{space 13}_cons {c |}{col 20}{res}{space 2}-.2091675{col 32}{space 2} 1.428746{col 43}{space 1}   -0.15{col 52}{space 3}0.884{col 60}{space 4}-3.009459{col 73}{space 3} 2.591124
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. *Wald p
. test AgeInteger Female Black Hispanic dpres nominate_dim1 ChamSeniority_Stew

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[born_inregion]AgeInteger = 0{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [born_inregion]Female = 0{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [born_inregion]Black = 0{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [born_inregion]Hispanic = 0{p_end}
{p 0 7}{space 1}{text:( 5)}{space 1} [born_inregion]dpres = 0{p_end}
{p 0 7}{space 1}{text:( 6)}{space 1} [born_inregion]nominate_dim1 = 0{p_end}
{p 0 7}{space 1}{text:( 7)}{space 1} [born_inregion]ChamSeniority_Stew = 0{p_end}

{txt}{col 12}chi2(  7) ={res}    3.99
{txt}{col 10}Prob > chi2 =  {res}  0.7804
{txt}
{com}. 
. clear
{txt}
{com}. 
. 
. ************************************
. *Table 3 - Agreement Scores Models 
. ************************************
. 
. *Select directory
. use "House_AgreementScoreData.dta"
{txt}(Written by R.              )

{com}. gen BirthDistanceMiles=BirthDistance/1609.34
{txt}
{com}. gen RepDistanceMiles=RepDistance/1609.34
{txt}
{com}. 
. *Best fitting model (Model 6) must be executed first
. quietly fracreg logit Agree c.Age##i.BirthRegion c.Age##c.BirthDistanceMiles RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}
{com}. quietly estat ic
{txt}
{com}. quietly mat s=r(S)
{txt}
{com}. quietly scalar aic6=s[1,5]
{txt}
{com}. quietly di aic6-aic6
{txt}
{com}. quietly scalar aicc6=aic6+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. quietly di aicc6-aicc6
{txt}
{com}. 
. *Model 1
. fracreg logit Agree c.Age##i.BirthState RepState Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-467000.89}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394511.79}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392168.97}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392159.77}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392159.77}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res}3861387.90
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392159.77{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}           Agree{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}Age {c |}{col 18}{res}{space 2} -.000955{col 30}{space 2} .0000664{col 41}{space 1}  -14.38{col 50}{space 3}0.000{col 58}{space 4}-.0010852{col 71}{space 3}-.0008248
{txt}{space 4}1.BirthState {c |}{col 18}{res}{space 2} .0172075{col 30}{space 2} .0048642{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} .0076739{col 71}{space 3} .0267412
{txt}{space 16} {c |}
BirthState#c.Age {c |}
{space 14}1  {c |}{col 18}{res}{space 2}-.0005057{col 30}{space 2} .0003137{col 41}{space 1}   -1.61{col 50}{space 3}0.107{col 58}{space 4}-.0011206{col 71}{space 3} .0001091
{txt}{space 16} {c |}
{space 8}RepState {c |}{col 18}{res}{space 2} .0385961{col 30}{space 2} .0031597{col 41}{space 1}   12.22{col 50}{space 3}0.000{col 58}{space 4} .0324033{col 71}{space 3}  .044789
{txt}{space 11}Party {c |}{col 18}{res}{space 2} 2.427982{col 30}{space 2} .0015111{col 41}{space 1} 1606.73{col 50}{space 3}0.000{col 58}{space 4}  2.42502{col 71}{space 3} 2.430944
{txt}{space 10}Gender {c |}{col 18}{res}{space 2}   .01677{col 30}{space 2} .0011432{col 41}{space 1}   14.67{col 50}{space 3}0.000{col 58}{space 4} .0145294{col 71}{space 3} .0190105
{txt}{space 12}Race {c |}{col 18}{res}{space 2}-.0542913{col 30}{space 2} .0012135{col 41}{space 1}  -44.74{col 50}{space 3}0.000{col 58}{space 4}-.0566698{col 71}{space 3}-.0519129
{txt}{space 11}DPres {c |}{col 18}{res}{space 2} -.012225{col 30}{space 2} .0000452{col 41}{space 1} -270.45{col 50}{space 3}0.000{col 58}{space 4}-.0123136{col 71}{space 3}-.0121364
{txt}{space 3}ChamSeniority {c |}{col 18}{res}{space 2}-.0031406{col 30}{space 2} .0001359{col 41}{space 1}  -23.11{col 50}{space 3}0.000{col 58}{space 4}-.0034069{col 71}{space 3}-.0028742
{txt}{space 16} {c |}
{space 8}congress {c |}
{space 12}108  {c |}{col 18}{res}{space 2}-.1219992{col 30}{space 2} .0021665{col 41}{space 1}  -56.31{col 50}{space 3}0.000{col 58}{space 4}-.1262455{col 71}{space 3} -.117753
{txt}{space 12}109  {c |}{col 18}{res}{space 2}-.2451017{col 30}{space 2}  .002255{col 41}{space 1} -108.69{col 50}{space 3}0.000{col 58}{space 4}-.2495214{col 71}{space 3}-.2406821
{txt}{space 12}110  {c |}{col 18}{res}{space 2}-.3314286{col 30}{space 2} .0023111{col 41}{space 1} -143.41{col 50}{space 3}0.000{col 58}{space 4}-.3359583{col 71}{space 3}-.3268988
{txt}{space 12}111  {c |}{col 18}{res}{space 2} .0773122{col 30}{space 2} .0022988{col 41}{space 1}   33.63{col 50}{space 3}0.000{col 58}{space 4} .0728065{col 71}{space 3} .0818178
{txt}{space 12}112  {c |}{col 18}{res}{space 2}-.7980919{col 30}{space 2} .0026251{col 41}{space 1} -304.02{col 50}{space 3}0.000{col 58}{space 4} -.803237{col 71}{space 3}-.7929468
{txt}{space 12}113  {c |}{col 18}{res}{space 2}-.6818715{col 30}{space 2} .0022468{col 41}{space 1} -303.49{col 50}{space 3}0.000{col 58}{space 4}-.6862751{col 71}{space 3}-.6774678
{txt}{space 12}114  {c |}{col 18}{res}{space 2}-.7265109{col 30}{space 2} .0025931{col 41}{space 1} -280.17{col 50}{space 3}0.000{col 58}{space 4}-.7315933{col 71}{space 3}-.7214285
{txt}{space 12}115  {c |}{col 18}{res}{space 2}-.5425325{col 30}{space 2} .0026196{col 41}{space 1} -207.11{col 50}{space 3}0.000{col 58}{space 4}-.5476667{col 71}{space 3}-.5373982
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .3919391{col 30}{space 2} .0025025{col 41}{space 1}  156.62{col 50}{space 3}0.000{col 58}{space 4} .3870342{col 71}{space 3} .3968439
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392159.8{col 49}    18{col 58} 784355.5{col 69} 784564.2
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic1=s[1,5]
{txt}
{com}. di aic1-aic6
{res}41.386101
{txt}
{com}. scalar aicc1=aic1+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C16=aicc1-aicc6
{txt}
{com}. *Change in AICc
. di C16
{res}41.385816
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##i.BirthState RepState Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Statistically significant difference between in-out birth state for all except the highest category of age
. 
. *Model 2
. fracreg logit Agree c.Age##i.BirthRegion RepRegion Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466996.34}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394498.33}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392155.54}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392146.34}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392146.34}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res}3861217.69
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392146.34{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}            Agree{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Age {c |}{col 19}{res}{space 2}-.0008669{col 31}{space 2} .0000702{col 42}{space 1}  -12.35{col 51}{space 3}0.000{col 59}{space 4}-.0010045{col 72}{space 3}-.0007292
{txt}{space 4}1.BirthRegion {c |}{col 19}{res}{space 2} .0195672{col 31}{space 2} .0026397{col 42}{space 1}    7.41{col 51}{space 3}0.000{col 59}{space 4} .0143935{col 72}{space 3} .0247409
{txt}{space 17} {c |}
BirthRegion#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2}-.0007969{col 31}{space 2} .0001691{col 42}{space 1}   -4.71{col 51}{space 3}0.000{col 59}{space 4}-.0011284{col 72}{space 3}-.0004654
{txt}{space 17} {c |}
{space 8}RepRegion {c |}{col 19}{res}{space 2} .0397514{col 31}{space 2} .0017442{col 42}{space 1}   22.79{col 51}{space 3}0.000{col 59}{space 4} .0363328{col 72}{space 3}   .04317
{txt}{space 12}Party {c |}{col 19}{res}{space 2} 2.427689{col 31}{space 2} .0015101{col 42}{space 1} 1607.62{col 51}{space 3}0.000{col 59}{space 4} 2.424729{col 72}{space 3} 2.430649
{txt}{space 11}Gender {c |}{col 19}{res}{space 2} .0153885{col 31}{space 2} .0011425{col 42}{space 1}   13.47{col 51}{space 3}0.000{col 59}{space 4} .0131493{col 72}{space 3} .0176277
{txt}{space 13}Race {c |}{col 19}{res}{space 2}-.0521684{col 31}{space 2} .0012183{col 42}{space 1}  -42.82{col 51}{space 3}0.000{col 59}{space 4}-.0545562{col 72}{space 3}-.0497806
{txt}{space 12}DPres {c |}{col 19}{res}{space 2}-.0121693{col 31}{space 2} .0000452{col 42}{space 1} -269.42{col 51}{space 3}0.000{col 59}{space 4}-.0122578{col 72}{space 3}-.0120808
{txt}{space 4}ChamSeniority {c |}{col 19}{res}{space 2}-.0030942{col 31}{space 2} .0001359{col 42}{space 1}  -22.77{col 51}{space 3}0.000{col 59}{space 4}-.0033605{col 72}{space 3}-.0028279
{txt}{space 17} {c |}
{space 9}congress {c |}
{space 13}108  {c |}{col 19}{res}{space 2}-.1220873{col 31}{space 2} .0021644{col 42}{space 1}  -56.41{col 51}{space 3}0.000{col 59}{space 4}-.1263295{col 72}{space 3} -.117845
{txt}{space 13}109  {c |}{col 19}{res}{space 2}-.2451463{col 31}{space 2} .0022529{col 42}{space 1} -108.81{col 51}{space 3}0.000{col 59}{space 4}-.2495619{col 72}{space 3}-.2407306
{txt}{space 13}110  {c |}{col 19}{res}{space 2}-.3315942{col 31}{space 2} .0023103{col 42}{space 1} -143.53{col 51}{space 3}0.000{col 59}{space 4}-.3361223{col 72}{space 3}-.3270662
{txt}{space 13}111  {c |}{col 19}{res}{space 2} .0771784{col 31}{space 2} .0022974{col 42}{space 1}   33.59{col 51}{space 3}0.000{col 59}{space 4} .0726756{col 72}{space 3} .0816812
{txt}{space 13}112  {c |}{col 19}{res}{space 2}-.7980683{col 31}{space 2} .0026222{col 42}{space 1} -304.35{col 51}{space 3}0.000{col 59}{space 4}-.8032078{col 72}{space 3}-.7929288
{txt}{space 13}113  {c |}{col 19}{res}{space 2} -.682227{col 31}{space 2} .0022441{col 42}{space 1} -304.01{col 51}{space 3}0.000{col 59}{space 4}-.6866254{col 72}{space 3}-.6778287
{txt}{space 13}114  {c |}{col 19}{res}{space 2} -.726821{col 31}{space 2} .0025919{col 42}{space 1} -280.42{col 51}{space 3}0.000{col 59}{space 4}-.7319011{col 72}{space 3} -.721741
{txt}{space 13}115  {c |}{col 19}{res}{space 2}-.5426612{col 31}{space 2} .0026181{col 42}{space 1} -207.27{col 51}{space 3}0.000{col 59}{space 4}-.5477926{col 72}{space 3}-.5375298
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2} .3833477{col 31}{space 2} .0025364{col 42}{space 1}  151.14{col 51}{space 3}0.000{col 59}{space 4} .3783764{col 72}{space 3}  .388319
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392146.3{col 49}    18{col 58} 784328.7{col 69} 784537.3
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic2=s[1,5]
{txt}
{com}. di aic2-aic6
{res}14.528856
{txt}
{com}. scalar aicc2=aic2+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C26=aicc2-aicc6
{txt}
{com}. *Change in AICc
. di C26
{res}14.528571
{txt}
{com}. 
. *Model 3
. fracreg logit Agree c.Age##c.BirthDistanceMiles RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466994.69}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394494.69}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392152.19}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392142.99}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392142.99}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res}3849106.65
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392142.99{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0014189{col 40}{space 2} .0001154{col 51}{space 1}  -12.29{col 60}{space 3}0.000{col 68}{space 4}-.0016452{col 81}{space 3}-.0011926
{txt}{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000117{col 40}{space 2} 1.49e-06{col 51}{space 1}   -7.81{col 60}{space 3}0.000{col 68}{space 4}-.0000146{col 81}{space 3}-8.75e-06
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 4.20e-07{col 40}{space 2} 9.29e-08{col 51}{space 1}    4.52{col 60}{space 3}0.000{col 68}{space 4} 2.38e-07{col 81}{space 3} 6.02e-07
{txt}{space 26} {c |}
{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-.0000223{col 40}{space 2} 9.91e-07{col 51}{space 1}  -22.50{col 60}{space 3}0.000{col 68}{space 4}-.0000242{col 81}{space 3}-.0000203
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.427811{col 40}{space 2} .0015107{col 51}{space 1} 1607.10{col 60}{space 3}0.000{col 68}{space 4}  2.42485{col 81}{space 3} 2.430772
{txt}{space 20}Gender {c |}{col 28}{res}{space 2} .0133363{col 40}{space 2} .0011431{col 51}{space 1}   11.67{col 60}{space 3}0.000{col 68}{space 4} .0110958{col 81}{space 3} .0155767
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0556643{col 40}{space 2} .0012145{col 51}{space 1}  -45.83{col 60}{space 3}0.000{col 68}{space 4}-.0580447{col 81}{space 3}-.0532839
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0121874{col 40}{space 2} .0000452{col 51}{space 1} -269.75{col 60}{space 3}0.000{col 68}{space 4}-.0122759{col 81}{space 3}-.0120988
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0031269{col 40}{space 2} .0001358{col 51}{space 1}  -23.03{col 60}{space 3}0.000{col 68}{space 4} -.003393{col 81}{space 3}-.0028608
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1215326{col 40}{space 2} .0021629{col 51}{space 1}  -56.19{col 60}{space 3}0.000{col 68}{space 4}-.1257719{col 81}{space 3}-.1172934
{txt}{space 22}109  {c |}{col 28}{res}{space 2}-.2445341{col 40}{space 2} .0022505{col 51}{space 1} -108.66{col 60}{space 3}0.000{col 68}{space 4}-.2489451{col 81}{space 3}-.2401232
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.3312982{col 40}{space 2}  .002308{col 51}{space 1} -143.55{col 60}{space 3}0.000{col 68}{space 4}-.3358217{col 81}{space 3}-.3267747
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .0778053{col 40}{space 2} .0022949{col 51}{space 1}   33.90{col 60}{space 3}0.000{col 68}{space 4} .0733074{col 81}{space 3} .0823032
{txt}{space 22}112  {c |}{col 28}{res}{space 2}-.7972496{col 40}{space 2} .0026201{col 51}{space 1} -304.29{col 60}{space 3}0.000{col 68}{space 4}-.8023848{col 81}{space 3}-.7921144
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6810058{col 40}{space 2} .0022437{col 51}{space 1} -303.52{col 60}{space 3}0.000{col 68}{space 4}-.6854034{col 81}{space 3}-.6766082
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.7258585{col 40}{space 2} .0025927{col 51}{space 1} -279.96{col 60}{space 3}0.000{col 68}{space 4}-.7309402{col 81}{space 3}-.7207769
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5420167{col 40}{space 2} .0026174{col 51}{space 1} -207.08{col 60}{space 3}0.000{col 68}{space 4}-.5471468{col 81}{space 3}-.5368866
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4325382{col 40}{space 2} .0028577{col 51}{space 1}  151.36{col 60}{space 3}0.000{col 68}{space 4} .4269373{col 81}{space 3} .4381392
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}  -392143{col 49}    18{col 58}   784322{col 69} 784530.7
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic3=s[1,5]
{txt}
{com}. di aic3-aic6
{res}7.8374919
{txt}
{com}. scalar aicc3=aic3+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C36=aicc3-aicc6
{txt}
{com}. *Change in AICc
. di C36
{res}7.8372068
{txt}
{com}. 
. *Model 4
. fracreg logit Agree c.Age##i.BirthState c.Age##i.BirthRegion RepState RepRegion Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466996.33}  
Iteration 1:{space 3}log pseudolikelihood = {res: -394498.3}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392155.45}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392146.26}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392146.26}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res}3867580.43
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392146.26{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}            Agree{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Age {c |}{col 19}{res}{space 2}-.0008661{col 31}{space 2} .0000702{col 42}{space 1}  -12.34{col 51}{space 3}0.000{col 59}{space 4}-.0010038{col 72}{space 3}-.0007285
{txt}{space 5}1.BirthState {c |}{col 19}{res}{space 2} -.002207{col 31}{space 2}  .005511{col 42}{space 1}   -0.40{col 51}{space 3}0.689{col 59}{space 4}-.0130084{col 72}{space 3} .0085943
{txt}{space 17} {c |}
{space 1}BirthState#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2} .0002556{col 31}{space 2} .0003565{col 42}{space 1}    0.72{col 51}{space 3}0.473{col 59}{space 4}-.0004431{col 72}{space 3} .0009543
{txt}{space 17} {c |}
{space 14}Age {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 4}1.BirthRegion {c |}{col 19}{res}{space 2} .0201951{col 31}{space 2} .0029915{col 42}{space 1}    6.75{col 51}{space 3}0.000{col 59}{space 4} .0143318{col 72}{space 3} .0260584
{txt}{space 17} {c |}
BirthRegion#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2}-.0008577{col 31}{space 2} .0001922{col 42}{space 1}   -4.46{col 51}{space 3}0.000{col 59}{space 4}-.0012343{col 72}{space 3} -.000481
{txt}{space 17} {c |}
{space 9}RepState {c |}{col 19}{res}{space 2} .0056276{col 31}{space 2} .0035778{col 42}{space 1}    1.57{col 51}{space 3}0.116{col 59}{space 4}-.0013848{col 72}{space 3} .0126399
{txt}{space 8}RepRegion {c |}{col 19}{res}{space 2} .0382518{col 31}{space 2} .0019747{col 42}{space 1}   19.37{col 51}{space 3}0.000{col 59}{space 4} .0343815{col 72}{space 3} .0421222
{txt}{space 12}Party {c |}{col 19}{res}{space 2} 2.427688{col 31}{space 2}   .00151{col 42}{space 1} 1607.70{col 51}{space 3}0.000{col 59}{space 4} 2.424729{col 72}{space 3} 2.430648
{txt}{space 11}Gender {c |}{col 19}{res}{space 2} .0154849{col 31}{space 2} .0011433{col 42}{space 1}   13.54{col 51}{space 3}0.000{col 59}{space 4} .0132441{col 72}{space 3} .0177258
{txt}{space 13}Race {c |}{col 19}{res}{space 2}-.0521409{col 31}{space 2} .0012184{col 42}{space 1}  -42.79{col 51}{space 3}0.000{col 59}{space 4} -.054529{col 72}{space 3}-.0497529
{txt}{space 12}DPres {c |}{col 19}{res}{space 2}-.0121691{col 31}{space 2} .0000452{col 42}{space 1} -269.36{col 51}{space 3}0.000{col 59}{space 4}-.0122576{col 72}{space 3}-.0120805
{txt}{space 4}ChamSeniority {c |}{col 19}{res}{space 2}-.0030984{col 31}{space 2} .0001358{col 42}{space 1}  -22.81{col 51}{space 3}0.000{col 59}{space 4}-.0033646{col 72}{space 3}-.0028322
{txt}{space 17} {c |}
{space 9}congress {c |}
{space 13}108  {c |}{col 19}{res}{space 2}-.1220853{col 31}{space 2} .0021645{col 42}{space 1}  -56.40{col 51}{space 3}0.000{col 59}{space 4}-.1263277{col 72}{space 3} -.117843
{txt}{space 13}109  {c |}{col 19}{res}{space 2} -.245146{col 31}{space 2}  .002253{col 42}{space 1} -108.81{col 51}{space 3}0.000{col 59}{space 4}-.2495618{col 72}{space 3}-.2407302
{txt}{space 13}110  {c |}{col 19}{res}{space 2} -.331585{col 31}{space 2} .0023103{col 42}{space 1} -143.52{col 51}{space 3}0.000{col 59}{space 4}-.3361131{col 72}{space 3}-.3270568
{txt}{space 13}111  {c |}{col 19}{res}{space 2} .0771769{col 31}{space 2} .0022975{col 42}{space 1}   33.59{col 51}{space 3}0.000{col 59}{space 4} .0726739{col 72}{space 3} .0816799
{txt}{space 13}112  {c |}{col 19}{res}{space 2}-.7980726{col 31}{space 2} .0026224{col 42}{space 1} -304.33{col 51}{space 3}0.000{col 59}{space 4}-.8032125{col 72}{space 3}-.7929328
{txt}{space 13}113  {c |}{col 19}{res}{space 2}-.6822173{col 31}{space 2} .0022444{col 42}{space 1} -303.96{col 51}{space 3}0.000{col 59}{space 4}-.6866163{col 72}{space 3}-.6778183
{txt}{space 13}114  {c |}{col 19}{res}{space 2}-.7268187{col 31}{space 2}  .002592{col 42}{space 1} -280.41{col 51}{space 3}0.000{col 59}{space 4}-.7318988{col 72}{space 3}-.7217385
{txt}{space 13}115  {c |}{col 19}{res}{space 2}-.5426543{col 31}{space 2} .0026183{col 42}{space 1} -207.25{col 51}{space 3}0.000{col 59}{space 4}-.5477861{col 72}{space 3}-.5375225
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2}  .383255{col 31}{space 2} .0025364{col 42}{space 1}  151.10{col 51}{space 3}0.000{col 59}{space 4} .3782837{col 72}{space 3} .3882262
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392146.3{col 49}    21{col 58} 784334.5{col 69}   784578
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic4=s[1,5]
{txt}
{com}. di aic4-aic6
{res}20.366841
{txt}
{com}. scalar aicc4=aic4+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C46=aicc4-aicc6
{txt}
{com}. *Change in AICc
. di C46
{res}20.366841
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##i.BirthState c.Age##i.BirthRegion RepState RepRegion Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Not statistically significant at any level of age
. 
. 
. *Model 5
. fracreg logit Agree c.Age##i.BirthState c.Age##c.BirthDistanceMiles RepState RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466994.52}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394493.79}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392151.08}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392141.89}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392141.89}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res}3862657.33
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392141.89{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0014043{col 40}{space 2} .0001219{col 51}{space 1}  -11.52{col 60}{space 3}0.000{col 68}{space 4}-.0016432{col 81}{space 3}-.0011654
{txt}{space 14}1.BirthState {c |}{col 28}{res}{space 2} .0036612{col 40}{space 2} .0050445{col 51}{space 1}    0.73{col 60}{space 3}0.468{col 68}{space 4}-.0062258{col 81}{space 3} .0135482
{txt}{space 26} {c |}
{space 10}BirthState#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0001378{col 40}{space 2} .0003252{col 51}{space 1}   -0.42{col 60}{space 3}0.672{col 68}{space 4}-.0007753{col 81}{space 3} .0004996
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000122{col 40}{space 2} 1.56e-06{col 51}{space 1}   -7.81{col 60}{space 3}0.000{col 68}{space 4}-.0000152{col 81}{space 3}-9.10e-06
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 4.13e-07{col 40}{space 2} 9.64e-08{col 51}{space 1}    4.29{col 60}{space 3}0.000{col 68}{space 4} 2.24e-07{col 81}{space 3} 6.02e-07
{txt}{space 26} {c |}
{space 18}RepState {c |}{col 28}{res}{space 2} .0208172{col 40}{space 2} .0033052{col 51}{space 1}    6.30{col 60}{space 3}0.000{col 68}{space 4}  .014339{col 81}{space 3} .0272954
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-.0000202{col 40}{space 2} 1.04e-06{col 51}{space 1}  -19.44{col 60}{space 3}0.000{col 68}{space 4}-.0000222{col 81}{space 3}-.0000181
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.427772{col 40}{space 2} .0015104{col 51}{space 1} 1607.38{col 60}{space 3}0.000{col 68}{space 4} 2.424812{col 81}{space 3} 2.430732
{txt}{space 20}Gender {c |}{col 28}{res}{space 2} .0138281{col 40}{space 2} .0011442{col 51}{space 1}   12.09{col 60}{space 3}0.000{col 68}{space 4} .0115854{col 81}{space 3} .0160707
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0552589{col 40}{space 2} .0012152{col 51}{space 1}  -45.47{col 60}{space 3}0.000{col 68}{space 4}-.0576407{col 81}{space 3}-.0528772
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0121827{col 40}{space 2} .0000452{col 51}{space 1} -269.72{col 60}{space 3}0.000{col 68}{space 4}-.0122712{col 81}{space 3}-.0120942
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0031376{col 40}{space 2} .0001357{col 51}{space 1}  -23.11{col 60}{space 3}0.000{col 68}{space 4}-.0034037{col 81}{space 3}-.0028716
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2} -.121558{col 40}{space 2} .0021632{col 51}{space 1}  -56.19{col 60}{space 3}0.000{col 68}{space 4}-.1257978{col 81}{space 3}-.1173182
{txt}{space 22}109  {c |}{col 28}{res}{space 2} -.244582{col 40}{space 2} .0022508{col 51}{space 1} -108.66{col 60}{space 3}0.000{col 68}{space 4}-.2489936{col 81}{space 3}-.2401705
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.3312991{col 40}{space 2} .0023084{col 51}{space 1} -143.52{col 60}{space 3}0.000{col 68}{space 4}-.3358234{col 81}{space 3}-.3267748
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .0777626{col 40}{space 2} .0022955{col 51}{space 1}   33.88{col 60}{space 3}0.000{col 68}{space 4} .0732635{col 81}{space 3} .0822616
{txt}{space 22}112  {c |}{col 28}{res}{space 2} -.797312{col 40}{space 2} .0026207{col 51}{space 1} -304.24{col 60}{space 3}0.000{col 68}{space 4}-.8024484{col 81}{space 3}-.7921756
{txt}{space 22}113  {c |}{col 28}{res}{space 2} -.681029{col 40}{space 2} .0022443{col 51}{space 1} -303.44{col 60}{space 3}0.000{col 68}{space 4}-.6854278{col 81}{space 3}-.6766302
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.7258881{col 40}{space 2} .0025931{col 51}{space 1} -279.93{col 60}{space 3}0.000{col 68}{space 4}-.7309705{col 81}{space 3}-.7208057
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5420286{col 40}{space 2} .0026176{col 51}{space 1} -207.07{col 60}{space 3}0.000{col 68}{space 4}-.5471589{col 81}{space 3}-.5368983
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4290108{col 40}{space 2} .0029158{col 51}{space 1}  147.13{col 60}{space 3}0.000{col 68}{space 4} .4232958{col 81}{space 3} .4347257
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392141.9{col 49}    21{col 58} 784325.8{col 69} 784569.2
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic5=s[1,5]
{txt}
{com}. di aic5-aic6
{res}11.619546
{txt}
{com}. scalar aicc5=aic5+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C56=aicc5-aicc6
{txt}
{com}. *Change in AICc
. di C56
{res}11.619546
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##BirthState c.Age##c.BirthDistanceMiles RepState RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Not statistically significant at any level of age
. 
. *Model 6
. *BEST FIT (using AIC and AICc, which converge on large n)
. fracreg logit Agree c.Age##i.BirthRegion c.Age##c.BirthDistanceMiles RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466992.65}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394488.01}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392145.27}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392136.08}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392136.08}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res}3861414.95
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392136.08{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0012404{col 40}{space 2} .0001353{col 51}{space 1}   -9.17{col 60}{space 3}0.000{col 68}{space 4}-.0015055{col 81}{space 3}-.0009753
{txt}{space 13}1.BirthRegion {c |}{col 28}{res}{space 2} .0095481{col 40}{space 2} .0028778{col 51}{space 1}    3.32{col 60}{space 3}0.001{col 68}{space 4} .0039078{col 81}{space 3} .0151885
{txt}{space 26} {c |}
{space 9}BirthRegion#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2} -.000533{col 40}{space 2} .0001848{col 51}{space 1}   -2.88{col 60}{space 3}0.004{col 68}{space 4}-.0008953{col 81}{space 3}-.0001708
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2} -.000011{col 40}{space 2} 1.63e-06{col 51}{space 1}   -6.73{col 60}{space 3}0.000{col 68}{space 4}-.0000142{col 81}{space 3}-7.79e-06
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 3.20e-07{col 40}{space 2} 1.02e-07{col 51}{space 1}    3.15{col 60}{space 3}0.002{col 68}{space 4} 1.21e-07{col 81}{space 3} 5.19e-07
{txt}{space 26} {c |}
{space 17}RepRegion {c |}{col 28}{res}{space 2} .0290128{col 40}{space 2} .0019137{col 51}{space 1}   15.16{col 60}{space 3}0.000{col 68}{space 4}  .025262{col 81}{space 3} .0327635
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-.0000151{col 40}{space 2} 1.09e-06{col 51}{space 1}  -13.85{col 60}{space 3}0.000{col 68}{space 4}-.0000172{col 81}{space 3}-.0000129
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.427608{col 40}{space 2} .0015098{col 51}{space 1} 1607.92{col 60}{space 3}0.000{col 68}{space 4} 2.424649{col 81}{space 3} 2.430567
{txt}{space 20}Gender {c |}{col 28}{res}{space 2} .0136032{col 40}{space 2} .0011432{col 51}{space 1}   11.90{col 60}{space 3}0.000{col 68}{space 4} .0113625{col 81}{space 3} .0158439
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0537104{col 40}{space 2} .0012203{col 51}{space 1}  -44.01{col 60}{space 3}0.000{col 68}{space 4}-.0561021{col 81}{space 3}-.0513186
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0121525{col 40}{space 2} .0000451{col 51}{space 1} -269.21{col 60}{space 3}0.000{col 68}{space 4} -.012241{col 81}{space 3} -.012064
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0031128{col 40}{space 2} .0001358{col 51}{space 1}  -22.93{col 60}{space 3}0.000{col 68}{space 4}-.0033789{col 81}{space 3}-.0028466
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1216981{col 40}{space 2} .0021625{col 51}{space 1}  -56.28{col 60}{space 3}0.000{col 68}{space 4}-.1259366{col 81}{space 3}-.1174596
{txt}{space 22}109  {c |}{col 28}{res}{space 2} -.244714{col 40}{space 2} .0022504{col 51}{space 1} -108.74{col 60}{space 3}0.000{col 68}{space 4}-.2491248{col 81}{space 3}-.2403033
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.3314274{col 40}{space 2} .0023084{col 51}{space 1} -143.57{col 60}{space 3}0.000{col 68}{space 4}-.3359517{col 81}{space 3} -.326903
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .0776067{col 40}{space 2} .0022952{col 51}{space 1}   33.81{col 60}{space 3}0.000{col 68}{space 4} .0731082{col 81}{space 3} .0821052
{txt}{space 22}112  {c |}{col 28}{res}{space 2} -.797435{col 40}{space 2} .0026196{col 51}{space 1} -304.41{col 60}{space 3}0.000{col 68}{space 4}-.8025693{col 81}{space 3}-.7923007
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6814063{col 40}{space 2}  .002243{col 51}{space 1} -303.79{col 60}{space 3}0.000{col 68}{space 4}-.6858025{col 81}{space 3}-.6770101
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.7261949{col 40}{space 2} .0025921{col 51}{space 1} -280.15{col 60}{space 3}0.000{col 68}{space 4}-.7312754{col 81}{space 3}-.7211144
{txt}{space 22}115  {c |}{col 28}{res}{space 2} -.542211{col 40}{space 2} .0026171{col 51}{space 1} -207.18{col 60}{space 3}0.000{col 68}{space 4}-.5473404{col 81}{space 3}-.5370816
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4158217{col 40}{space 2} .0030678{col 51}{space 1}  135.55{col 60}{space 3}0.000{col 68}{space 4}  .409809{col 81}{space 3} .4218344
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392136.1{col 49}    21{col 58} 784314.2{col 69} 784557.6
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic6=s[1,5]
{txt}
{com}. di aic6-aic6
{res}0
{txt}
{com}. scalar aicc6=aic6+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C66=aicc6-aicc6
{txt}
{com}. *Change in AICc
. di C66
{res}0
{txt}
{com}. 
. *Model 7
. fracreg logit Agree c.Age##i.BirthState c.Age##i.BirthRegion c.Age##c.BirthDistanceMiles RepState RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity
note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-466992.61}  
Iteration 1:{space 3}log pseudolikelihood = {res:-394488.01}  
Iteration 2:{space 3}log pseudolikelihood = {res:-392145.25}  
Iteration 3:{space 3}log pseudolikelihood = {res:-392136.05}  
Iteration 4:{space 3}log pseudolikelihood = {res:-392136.05}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   799,994
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res}3868304.33
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-392136.05{txt}{col 49}Pseudo R2{col 67}= {res}    0.2306

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0012505{col 40}{space 2} .0001357{col 51}{space 1}   -9.22{col 60}{space 3}0.000{col 68}{space 4}-.0015164{col 81}{space 3}-.0009845
{txt}{space 14}1.BirthState {c |}{col 28}{res}{space 2}-.0056725{col 40}{space 2} .0055372{col 51}{space 1}   -1.02{col 60}{space 3}0.306{col 68}{space 4}-.0165252{col 81}{space 3} .0051802
{txt}{space 26} {c |}
{space 10}BirthState#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2} .0003268{col 40}{space 2} .0003578{col 51}{space 1}    0.91{col 60}{space 3}0.361{col 68}{space 4}-.0003745{col 81}{space 3} .0010281
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 13}1.BirthRegion {c |}{col 28}{res}{space 2} .0108889{col 40}{space 2} .0031573{col 51}{space 1}    3.45{col 60}{space 3}0.001{col 68}{space 4} .0047008{col 81}{space 3}  .017077
{txt}{space 26} {c |}
{space 9}BirthRegion#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0006082{col 40}{space 2} .0002033{col 51}{space 1}   -2.99{col 60}{space 3}0.003{col 68}{space 4}-.0010066{col 81}{space 3}-.0002098
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000112{col 40}{space 2} 1.64e-06{col 51}{space 1}   -6.80{col 60}{space 3}0.000{col 68}{space 4}-.0000144{col 81}{space 3}-7.95e-06
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 3.29e-07{col 40}{space 2} 1.02e-07{col 51}{space 1}    3.23{col 60}{space 3}0.001{col 68}{space 4} 1.29e-07{col 81}{space 3} 5.29e-07
{txt}{space 26} {c |}
{space 18}RepState {c |}{col 28}{res}{space 2} .0006935{col 40}{space 2} .0036058{col 51}{space 1}    0.19{col 60}{space 3}0.847{col 68}{space 4}-.0063739{col 81}{space 3} .0077608
{txt}{space 17}RepRegion {c |}{col 28}{res}{space 2} .0288351{col 40}{space 2}  .002087{col 51}{space 1}   13.82{col 60}{space 3}0.000{col 68}{space 4} .0247447{col 81}{space 3} .0329256
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2} -.000015{col 40}{space 2} 1.10e-06{col 51}{space 1}  -13.70{col 60}{space 3}0.000{col 68}{space 4}-.0000172{col 81}{space 3}-.0000129
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.427609{col 40}{space 2} .0015097{col 51}{space 1} 1607.98{col 60}{space 3}0.000{col 68}{space 4}  2.42465{col 81}{space 3} 2.430568
{txt}{space 20}Gender {c |}{col 28}{res}{space 2} .0136063{col 40}{space 2} .0011442{col 51}{space 1}   11.89{col 60}{space 3}0.000{col 68}{space 4} .0113638{col 81}{space 3} .0158488
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0537012{col 40}{space 2} .0012203{col 51}{space 1}  -44.01{col 60}{space 3}0.000{col 68}{space 4}-.0560929{col 81}{space 3}-.0513095
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0121524{col 40}{space 2} .0000452{col 51}{space 1} -269.10{col 60}{space 3}0.000{col 68}{space 4}-.0122409{col 81}{space 3}-.0120639
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0031125{col 40}{space 2} .0001357{col 51}{space 1}  -22.93{col 60}{space 3}0.000{col 68}{space 4}-.0033786{col 81}{space 3}-.0028465
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1216977{col 40}{space 2} .0021625{col 51}{space 1}  -56.28{col 60}{space 3}0.000{col 68}{space 4}-.1259363{col 81}{space 3}-.1174592
{txt}{space 22}109  {c |}{col 28}{res}{space 2} -.244712{col 40}{space 2} .0022504{col 51}{space 1} -108.74{col 60}{space 3}0.000{col 68}{space 4}-.2491228{col 81}{space 3}-.2403013
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.3314248{col 40}{space 2} .0023084{col 51}{space 1} -143.57{col 60}{space 3}0.000{col 68}{space 4}-.3359492{col 81}{space 3}-.3269003
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .0776063{col 40}{space 2} .0022953{col 51}{space 1}   33.81{col 60}{space 3}0.000{col 68}{space 4} .0731076{col 81}{space 3}  .082105
{txt}{space 22}112  {c |}{col 28}{res}{space 2}-.7974287{col 40}{space 2} .0026197{col 51}{space 1} -304.40{col 60}{space 3}0.000{col 68}{space 4}-.8025633{col 81}{space 3}-.7922942
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6814071{col 40}{space 2} .0022433{col 51}{space 1} -303.75{col 60}{space 3}0.000{col 68}{space 4}-.6858039{col 81}{space 3}-.6770102
{txt}{space 22}114  {c |}{col 28}{res}{space 2} -.726198{col 40}{space 2} .0025923{col 51}{space 1} -280.14{col 60}{space 3}0.000{col 68}{space 4}-.7312788{col 81}{space 3}-.7211172
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5422063{col 40}{space 2} .0026172{col 51}{space 1} -207.17{col 60}{space 3}0.000{col 68}{space 4}-.5473359{col 81}{space 3}-.5370767
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4159513{col 40}{space 2} .0030695{col 51}{space 1}  135.51{col 60}{space 3}0.000{col 68}{space 4} .4099352{col 81}{space 3} .4219673
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   799,994{col 27}-509669.6{col 38}-392136.1{col 49}    24{col 58} 784320.1{col 69} 784598.3
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic7=s[1,5]
{txt}
{com}. di aic7-aic6
{res}5.9582645
{txt}
{com}. scalar aicc7=aic7+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C76=aicc7-aicc6
{txt}
{com}. *Change in AICc
. di C76
{res}5.9585945
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##BirthState c.Age##BirthRegion c.Age##c.BirthDistanceMiles RepState RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Not statistically significant at any level of age
. 
. *Calculating w_i (i.e., Probability of best model)
. scalar E1=exp(-.5*C16)
{txt}
{com}. scalar E2=exp(-.5*C26)
{txt}
{com}. scalar E3=exp(-.5*C36)
{txt}
{com}. scalar E4=exp(-.5*C46)
{txt}
{com}. scalar E5=exp(-.5*C56)
{txt}
{com}. scalar E6=exp(-.5*C66)
{txt}
{com}. scalar E7=exp(-.5*C76)
{txt}
{com}. 
. scalar W1=(E1)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W2=(E2)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W3=(E3)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W4=(E4)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W5=(E5)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W6=(E6)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W7=(E7)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. 
. di W1
{res}9.594e-10
{txt}
{com}. di W2
{res}.0006516
{txt}
{com}. di W3
{res}.01849237
{txt}
{com}. di W4
{res}.00003517
{txt}
{com}. di W5
{res}.00279041
{txt}
{com}. di W6
{res}.93072314
{txt}
{com}. di W7
{res}.0473073
{txt}
{com}. 
. clear
{txt}
{com}. 
. 
. ************************************************************
. *Agreement Scores Models, High School Restriction - Table 4
. ************************************************************
. 
. *Same analysis as above, but restricting observations to those members who attended high school in the same county as their birth.
. 
. *Select directory
. use "House_AgreementScoreData.dta"
{txt}(Written by R.              )

{com}. keep if HSsamecountyMin==1 & HSsamecountyMax==1
{txt}(622,365 observations deleted)

{com}. gen BirthDistanceMiles=BirthDistance/1609.34
{txt}
{com}. gen RepDistanceMiles=RepDistance/1609.34
{txt}
{com}. 
. *Best fitting model (Model 3) must be executed first
. quietly fracreg logit Agree c.Age##c.BirthDistanceMiles RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}
{com}. quietly estat ic
{txt}
{com}. quietly mat s=r(S)
{txt}
{com}. quietly scalar aic3=s[1,5]
{txt}
{com}. quietly di aic3-aic3
{txt}
{com}. quietly scalar aicc3=aic3+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. quietly di aicc3-aicc3
{txt}
{com}. 
. *Model 1
. fracreg logit Agree c.Age##i.BirthState RepState Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103499.33}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87595.201}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87072.311}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87070.345}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87070.345}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res} 863082.47
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87070.345{txt}{col 49}Pseudo R2{col 67}= {res}    0.2280

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}           Agree{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      z{col 50}   P>|z|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}Age {c |}{col 18}{res}{space 2}-.0011679{col 30}{space 2} .0001392{col 41}{space 1}   -8.39{col 50}{space 3}0.000{col 58}{space 4}-.0014408{col 71}{space 3} -.000895
{txt}{space 4}1.BirthState {c |}{col 18}{res}{space 2} .0338682{col 30}{space 2} .0119574{col 41}{space 1}    2.83{col 50}{space 3}0.005{col 58}{space 4} .0104321{col 71}{space 3} .0573042
{txt}{space 16} {c |}
BirthState#c.Age {c |}
{space 14}1  {c |}{col 18}{res}{space 2}-.0001366{col 30}{space 2} .0006336{col 41}{space 1}   -0.22{col 50}{space 3}0.829{col 58}{space 4}-.0013783{col 71}{space 3} .0011052
{txt}{space 16} {c |}
{space 8}RepState {c |}{col 18}{res}{space 2} .0154532{col 30}{space 2} .0086989{col 41}{space 1}    1.78{col 50}{space 3}0.076{col 58}{space 4}-.0015962{col 71}{space 3} .0325026
{txt}{space 11}Party {c |}{col 18}{res}{space 2} 2.400752{col 30}{space 2} .0031863{col 41}{space 1}  753.47{col 50}{space 3}0.000{col 58}{space 4} 2.394507{col 71}{space 3} 2.406997
{txt}{space 10}Gender {c |}{col 18}{res}{space 2} -.012284{col 30}{space 2} .0025709{col 41}{space 1}   -4.78{col 50}{space 3}0.000{col 58}{space 4}-.0173229{col 71}{space 3}-.0072451
{txt}{space 12}Race {c |}{col 18}{res}{space 2}-.0656652{col 30}{space 2} .0025136{col 41}{space 1}  -26.12{col 50}{space 3}0.000{col 58}{space 4}-.0705918{col 71}{space 3}-.0607386
{txt}{space 11}DPres {c |}{col 18}{res}{space 2} -.012783{col 30}{space 2}  .000095{col 41}{space 1} -134.50{col 50}{space 3}0.000{col 58}{space 4}-.0129693{col 71}{space 3}-.0125967
{txt}{space 3}ChamSeniority {c |}{col 18}{res}{space 2}-.0018184{col 30}{space 2} .0002984{col 41}{space 1}   -6.09{col 50}{space 3}0.000{col 58}{space 4}-.0024033{col 71}{space 3}-.0012334
{txt}{space 16} {c |}
{space 8}congress {c |}
{space 12}108  {c |}{col 18}{res}{space 2}-.1035962{col 30}{space 2} .0046373{col 41}{space 1}  -22.34{col 50}{space 3}0.000{col 58}{space 4}-.1126852{col 71}{space 3}-.0945073
{txt}{space 12}109  {c |}{col 18}{res}{space 2}-.2078569{col 30}{space 2} .0047121{col 41}{space 1}  -44.11{col 50}{space 3}0.000{col 58}{space 4}-.2170924{col 71}{space 3}-.1986214
{txt}{space 12}110  {c |}{col 18}{res}{space 2}-.2758913{col 30}{space 2} .0048708{col 41}{space 1}  -56.64{col 50}{space 3}0.000{col 58}{space 4}-.2854378{col 71}{space 3}-.2663447
{txt}{space 12}111  {c |}{col 18}{res}{space 2} .1099001{col 30}{space 2} .0049636{col 41}{space 1}   22.14{col 50}{space 3}0.000{col 58}{space 4} .1001715{col 71}{space 3} .1196286
{txt}{space 12}112  {c |}{col 18}{res}{space 2} -.822435{col 30}{space 2} .0051986{col 41}{space 1} -158.20{col 50}{space 3}0.000{col 58}{space 4} -.832624{col 71}{space 3} -.812246
{txt}{space 12}113  {c |}{col 18}{res}{space 2} -.655925{col 30}{space 2} .0049768{col 41}{space 1} -131.80{col 50}{space 3}0.000{col 58}{space 4}-.6656794{col 71}{space 3}-.6461706
{txt}{space 12}114  {c |}{col 18}{res}{space 2}-.6624674{col 30}{space 2} .0052513{col 41}{space 1} -126.15{col 50}{space 3}0.000{col 58}{space 4}-.6727597{col 71}{space 3}-.6521751
{txt}{space 12}115  {c |}{col 18}{res}{space 2}-.5148696{col 30}{space 2} .0055063{col 41}{space 1}  -93.51{col 50}{space 3}0.000{col 58}{space 4}-.5256617{col 71}{space 3}-.5040774
{txt}{space 16} {c |}
{space 11}_cons {c |}{col 18}{res}{space 2} .4095115{col 30}{space 2} .0052443{col 41}{space 1}   78.09{col 50}{space 3}0.000{col 58}{space 4} .3992328{col 71}{space 3} .4197901
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87070.34{col 49}    18{col 58} 174176.7{col 69} 174358.3
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic1=s[1,5]
{txt}
{com}. di aic1-aic3
{res}12.071359
{txt}
{com}. scalar aicc1=aic1+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C13=aicc1-aicc3
{txt}
{com}. *Change in AICc
. di C13
{res}12.071359
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##i.BirthState RepState Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Statistically significant difference between in-out birth state for all except the highest category of age
. 
. *Model 2
. fracreg logit Agree c.Age##i.BirthRegion RepRegion Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103498.55}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87593.101}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87070.257}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87068.292}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87068.292}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res} 862708.77
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87068.292{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}            Agree{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Age {c |}{col 19}{res}{space 2}-.0009606{col 31}{space 2} .0001486{col 42}{space 1}   -6.46{col 51}{space 3}0.000{col 59}{space 4}-.0012518{col 72}{space 3}-.0006693
{txt}{space 4}1.BirthRegion {c |}{col 19}{res}{space 2} .0522063{col 31}{space 2} .0062721{col 42}{space 1}    8.32{col 51}{space 3}0.000{col 59}{space 4} .0399131{col 72}{space 3} .0644994
{txt}{space 17} {c |}
BirthRegion#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2}-.0013834{col 31}{space 2} .0003309{col 42}{space 1}   -4.18{col 51}{space 3}0.000{col 59}{space 4} -.002032{col 72}{space 3}-.0007348
{txt}{space 17} {c |}
{space 8}RepRegion {c |}{col 19}{res}{space 2} .0039979{col 31}{space 2} .0047782{col 42}{space 1}    0.84{col 51}{space 3}0.403{col 59}{space 4}-.0053672{col 72}{space 3}  .013363
{txt}{space 12}Party {c |}{col 19}{res}{space 2} 2.400773{col 31}{space 2} .0031868{col 42}{space 1}  753.35{col 51}{space 3}0.000{col 59}{space 4} 2.394527{col 72}{space 3} 2.407019
{txt}{space 11}Gender {c |}{col 19}{res}{space 2} -.013011{col 31}{space 2} .0025671{col 42}{space 1}   -5.07{col 51}{space 3}0.000{col 59}{space 4}-.0180423{col 72}{space 3}-.0079797
{txt}{space 13}Race {c |}{col 19}{res}{space 2}-.0647451{col 31}{space 2} .0025177{col 42}{space 1}  -25.72{col 51}{space 3}0.000{col 59}{space 4}-.0696798{col 72}{space 3}-.0598105
{txt}{space 12}DPres {c |}{col 19}{res}{space 2}-.0127602{col 31}{space 2} .0000951{col 42}{space 1} -134.24{col 51}{space 3}0.000{col 59}{space 4}-.0129465{col 72}{space 3}-.0125739
{txt}{space 4}ChamSeniority {c |}{col 19}{res}{space 2}-.0017586{col 31}{space 2} .0002983{col 42}{space 1}   -5.90{col 51}{space 3}0.000{col 59}{space 4}-.0023432{col 72}{space 3} -.001174
{txt}{space 17} {c |}
{space 9}congress {c |}
{space 13}108  {c |}{col 19}{res}{space 2}-.1035713{col 31}{space 2} .0046364{col 42}{space 1}  -22.34{col 51}{space 3}0.000{col 59}{space 4}-.1126584{col 72}{space 3}-.0944841
{txt}{space 13}109  {c |}{col 19}{res}{space 2}-.2078014{col 31}{space 2} .0047108{col 42}{space 1}  -44.11{col 51}{space 3}0.000{col 59}{space 4}-.2170344{col 72}{space 3}-.1985685
{txt}{space 13}110  {c |}{col 19}{res}{space 2}-.2758315{col 31}{space 2} .0048703{col 42}{space 1}  -56.64{col 51}{space 3}0.000{col 59}{space 4}-.2853771{col 72}{space 3}-.2662859
{txt}{space 13}111  {c |}{col 19}{res}{space 2} .1099668{col 31}{space 2} .0049615{col 42}{space 1}   22.16{col 51}{space 3}0.000{col 59}{space 4} .1002424{col 72}{space 3} .1196912
{txt}{space 13}112  {c |}{col 19}{res}{space 2}-.8222728{col 31}{space 2} .0051959{col 42}{space 1} -158.26{col 51}{space 3}0.000{col 59}{space 4}-.8324565{col 72}{space 3} -.812089
{txt}{space 13}113  {c |}{col 19}{res}{space 2}  -.65592{col 31}{space 2} .0049734{col 42}{space 1} -131.89{col 51}{space 3}0.000{col 59}{space 4}-.6656677{col 72}{space 3}-.6461723
{txt}{space 13}114  {c |}{col 19}{res}{space 2}-.6625219{col 31}{space 2} .0052502{col 42}{space 1} -126.19{col 51}{space 3}0.000{col 59}{space 4}-.6728122{col 72}{space 3}-.6522317
{txt}{space 13}115  {c |}{col 19}{res}{space 2}-.5148064{col 31}{space 2} .0055054{col 42}{space 1}  -93.51{col 51}{space 3}0.000{col 59}{space 4}-.5255968{col 72}{space 3} -.504016
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2} .4018127{col 31}{space 2} .0053128{col 42}{space 1}   75.63{col 51}{space 3}0.000{col 59}{space 4} .3913998{col 72}{space 3} .4122256
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87068.29{col 49}    18{col 58} 174172.6{col 69} 174354.2
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic2=s[1,5]
{txt}
{com}. di aic2-aic3
{res}7.9657715
{txt}
{com}. scalar aicc2=aic2+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C23=aicc2-aicc3
{txt}
{com}. *Change in AICc
. di C23
{res}7.9657715
{txt}
{com}. 
. *Model 3
. *BEST FIT (using AIC and AICc, which converge on large n)
. fracreg logit Agree c.Age##c.BirthDistanceMiles RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103497.09}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87589.161}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87066.272}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87064.309}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87064.309}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}17{txt}){col 67}= {res} 861640.31
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87064.309{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0021857{col 40}{space 2} .0002437{col 51}{space 1}   -8.97{col 60}{space 3}0.000{col 68}{space 4}-.0026634{col 81}{space 3} -.001708
{txt}{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000345{col 40}{space 2} 3.83e-06{col 51}{space 1}   -8.99{col 60}{space 3}0.000{col 68}{space 4} -.000042{col 81}{space 3}-.0000269
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 9.75e-07{col 40}{space 2} 1.94e-07{col 51}{space 1}    5.03{col 60}{space 3}0.000{col 68}{space 4} 5.95e-07{col 81}{space 3} 1.36e-06
{txt}{space 26} {c |}
{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2} -.000011{col 40}{space 2} 2.95e-06{col 51}{space 1}   -3.73{col 60}{space 3}0.000{col 68}{space 4}-.0000168{col 81}{space 3}-5.22e-06
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.400743{col 40}{space 2} .0031867{col 51}{space 1}  753.36{col 60}{space 3}0.000{col 68}{space 4} 2.394497{col 81}{space 3} 2.406988
{txt}{space 20}Gender {c |}{col 28}{res}{space 2}-.0123326{col 40}{space 2} .0025692{col 51}{space 1}   -4.80{col 60}{space 3}0.000{col 68}{space 4}-.0173681{col 81}{space 3}-.0072971
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0709826{col 40}{space 2} .0025116{col 51}{space 1}  -28.26{col 60}{space 3}0.000{col 68}{space 4}-.0759053{col 81}{space 3}-.0660599
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0127878{col 40}{space 2} .0000951{col 51}{space 1} -134.48{col 60}{space 3}0.000{col 68}{space 4}-.0129742{col 81}{space 3}-.0126014
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0017619{col 40}{space 2} .0002985{col 51}{space 1}   -5.90{col 60}{space 3}0.000{col 68}{space 4}-.0023471{col 81}{space 3}-.0011768
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1021837{col 40}{space 2} .0046318{col 51}{space 1}  -22.06{col 60}{space 3}0.000{col 68}{space 4}-.1112618{col 81}{space 3}-.0931056
{txt}{space 22}109  {c |}{col 28}{res}{space 2}-.2066078{col 40}{space 2}  .004702{col 51}{space 1}  -43.94{col 60}{space 3}0.000{col 68}{space 4}-.2158235{col 81}{space 3}-.1973921
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.2744208{col 40}{space 2} .0048612{col 51}{space 1}  -56.45{col 60}{space 3}0.000{col 68}{space 4}-.2839486{col 81}{space 3}-.2648931
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .1120752{col 40}{space 2} .0049537{col 51}{space 1}   22.62{col 60}{space 3}0.000{col 68}{space 4} .1023662{col 81}{space 3} .1217842
{txt}{space 22}112  {c |}{col 28}{res}{space 2}-.8199026{col 40}{space 2} .0051902{col 51}{space 1} -157.97{col 60}{space 3}0.000{col 68}{space 4}-.8300752{col 81}{space 3}  -.80973
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6541317{col 40}{space 2} .0049757{col 51}{space 1} -131.46{col 60}{space 3}0.000{col 68}{space 4} -.663884{col 81}{space 3}-.6443794
{txt}{space 22}114  {c |}{col 28}{res}{space 2} -.661295{col 40}{space 2} .0052522{col 51}{space 1} -125.91{col 60}{space 3}0.000{col 68}{space 4}-.6715892{col 81}{space 3}-.6510008
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5140419{col 40}{space 2} .0054991{col 51}{space 1}  -93.48{col 60}{space 3}0.000{col 68}{space 4}  -.52482{col 81}{space 3}-.5032638
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4601926{col 40}{space 2} .0059843{col 51}{space 1}   76.90{col 60}{space 3}0.000{col 68}{space 4} .4484637{col 81}{space 3} .4719216
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87064.31{col 49}    18{col 58} 174164.6{col 69} 174346.2
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic3=s[1,5]
{txt}
{com}. di aic3-aic3
{res}0
{txt}
{com}. scalar aicc3=aic3+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C33=aicc3-aicc3
{txt}
{com}. *Change in AICc
. di C33
{res}0
{txt}
{com}. 
. *Model 4
. fracreg logit Agree c.Age##i.BirthState c.Age##i.BirthRegion RepState RepRegion Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -103498.5}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87592.936}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87070.065}  
Iteration 3:{space 3}log pseudolikelihood = {res:  -87068.1}  
Iteration 4:{space 3}log pseudolikelihood = {res:  -87068.1}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res} 863888.97
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}  -87068.1{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}            Agree{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      z{col 51}   P>|z|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}Age {c |}{col 19}{res}{space 2}-.0009591{col 31}{space 2} .0001486{col 42}{space 1}   -6.45{col 51}{space 3}0.000{col 59}{space 4}-.0012504{col 72}{space 3}-.0006678
{txt}{space 5}1.BirthState {c |}{col 19}{res}{space 2}-.0146392{col 31}{space 2} .0133579{col 42}{space 1}   -1.10{col 51}{space 3}0.273{col 59}{space 4}-.0408203{col 72}{space 3} .0115419
{txt}{space 17} {c |}
{space 1}BirthState#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2} .0013931{col 31}{space 2} .0007095{col 42}{space 1}    1.96{col 51}{space 3}0.050{col 59}{space 4} 2.52e-06{col 72}{space 3} .0027837
{txt}{space 17} {c |}
{space 14}Age {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 4}1.BirthRegion {c |}{col 19}{res}{space 2} .0563333{col 31}{space 2} .0069853{col 42}{space 1}    8.06{col 51}{space 3}0.000{col 59}{space 4} .0426424{col 72}{space 3} .0700241
{txt}{space 17} {c |}
BirthRegion#c.Age {c |}
{space 15}1  {c |}{col 19}{res}{space 2}-.0017409{col 31}{space 2} .0003704{col 42}{space 1}   -4.70{col 51}{space 3}0.000{col 59}{space 4}-.0024667{col 72}{space 3} -.001015
{txt}{space 17} {c |}
{space 9}RepState {c |}{col 19}{res}{space 2} .0143457{col 31}{space 2} .0098565{col 42}{space 1}    1.46{col 51}{space 3}0.146{col 59}{space 4}-.0049727{col 72}{space 3} .0336642
{txt}{space 8}RepRegion {c |}{col 19}{res}{space 2}-.0000897{col 31}{space 2}  .005408{col 42}{space 1}   -0.02{col 51}{space 3}0.987{col 59}{space 4}-.0106893{col 72}{space 3} .0105098
{txt}{space 12}Party {c |}{col 19}{res}{space 2} 2.400794{col 31}{space 2} .0031863{col 42}{space 1}  753.48{col 51}{space 3}0.000{col 59}{space 4} 2.394549{col 72}{space 3} 2.407039
{txt}{space 11}Gender {c |}{col 19}{res}{space 2}-.0126967{col 31}{space 2} .0025724{col 42}{space 1}   -4.94{col 51}{space 3}0.000{col 59}{space 4}-.0177385{col 72}{space 3}-.0076549
{txt}{space 13}Race {c |}{col 19}{res}{space 2}-.0646369{col 31}{space 2} .0025184{col 42}{space 1}  -25.67{col 51}{space 3}0.000{col 59}{space 4}-.0695728{col 72}{space 3} -.059701
{txt}{space 12}DPres {c |}{col 19}{res}{space 2}-.0127578{col 31}{space 2} .0000951{col 42}{space 1} -134.17{col 51}{space 3}0.000{col 59}{space 4}-.0129442{col 72}{space 3}-.0125715
{txt}{space 4}ChamSeniority {c |}{col 19}{res}{space 2}-.0017728{col 31}{space 2} .0002983{col 42}{space 1}   -5.94{col 51}{space 3}0.000{col 59}{space 4}-.0023574{col 72}{space 3}-.0011882
{txt}{space 17} {c |}
{space 9}congress {c |}
{space 13}108  {c |}{col 19}{res}{space 2}-.1035809{col 31}{space 2} .0046364{col 42}{space 1}  -22.34{col 51}{space 3}0.000{col 59}{space 4}-.1126681{col 72}{space 3}-.0944936
{txt}{space 13}109  {c |}{col 19}{res}{space 2}-.2078361{col 31}{space 2} .0047108{col 42}{space 1}  -44.12{col 51}{space 3}0.000{col 59}{space 4} -.217069{col 72}{space 3}-.1986031
{txt}{space 13}110  {c |}{col 19}{res}{space 2}-.2758482{col 31}{space 2} .0048705{col 42}{space 1}  -56.64{col 51}{space 3}0.000{col 59}{space 4}-.2853942{col 72}{space 3}-.2663022
{txt}{space 13}111  {c |}{col 19}{res}{space 2} .1099074{col 31}{space 2} .0049618{col 42}{space 1}   22.15{col 51}{space 3}0.000{col 59}{space 4} .1001825{col 72}{space 3} .1196323
{txt}{space 13}112  {c |}{col 19}{res}{space 2}-.8223461{col 31}{space 2} .0051957{col 42}{space 1} -158.27{col 51}{space 3}0.000{col 59}{space 4}-.8325295{col 72}{space 3}-.8121627
{txt}{space 13}113  {c |}{col 19}{res}{space 2}-.6559855{col 31}{space 2} .0049739{col 42}{space 1} -131.89{col 51}{space 3}0.000{col 59}{space 4}-.6657342{col 72}{space 3}-.6462369
{txt}{space 13}114  {c |}{col 19}{res}{space 2}-.6625711{col 31}{space 2} .0052506{col 42}{space 1} -126.19{col 51}{space 3}0.000{col 59}{space 4} -.672862{col 72}{space 3}-.6522801
{txt}{space 13}115  {c |}{col 19}{res}{space 2}-.5148709{col 31}{space 2} .0055054{col 42}{space 1}  -93.52{col 51}{space 3}0.000{col 59}{space 4}-.5256612{col 72}{space 3}-.5040805
{txt}{space 17} {c |}
{space 12}_cons {c |}{col 19}{res}{space 2} .4015358{col 31}{space 2} .0053155{col 42}{space 1}   75.54{col 51}{space 3}0.000{col 59}{space 4} .3911176{col 72}{space 3} .4119541
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38} -87068.1{col 49}    21{col 58} 174178.2{col 69}   174390
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic4=s[1,5]
{txt}
{com}. di aic4-aic3
{res}13.582001
{txt}
{com}. scalar aicc4=aic4+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C43=aicc4-aicc3
{txt}
{com}. *Change in AICc
. di C43
{res}13.583284
{txt}
{com}. 
. *Model 5
. fracreg logit Agree c.Age##i.BirthState c.Age##c.BirthDistanceMiles RepState RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103497.06}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87589.013}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87066.085}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87064.122}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87064.122}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res} 864963.58
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87064.122{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0023129{col 40}{space 2} .0002575{col 51}{space 1}   -8.98{col 60}{space 3}0.000{col 68}{space 4}-.0028176{col 81}{space 3}-.0018081
{txt}{space 14}1.BirthState {c |}{col 28}{res}{space 2} .0007061{col 40}{space 2}  .012404{col 51}{space 1}    0.06{col 60}{space 3}0.955{col 68}{space 4}-.0236052{col 81}{space 3} .0250174
{txt}{space 26} {c |}
{space 10}BirthState#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2} .0008112{col 40}{space 2} .0006584{col 51}{space 1}    1.23{col 60}{space 3}0.218{col 68}{space 4}-.0004792{col 81}{space 3} .0021015
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2} -.000035{col 40}{space 2} 3.99e-06{col 51}{space 1}   -8.77{col 60}{space 3}0.000{col 68}{space 4}-.0000428{col 81}{space 3}-.0000272
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 1.06e-06{col 40}{space 2} 2.02e-07{col 51}{space 1}    5.28{col 60}{space 3}0.000{col 68}{space 4} 6.69e-07{col 81}{space 3} 1.46e-06
{txt}{space 26} {c |}
{space 18}RepState {c |}{col 28}{res}{space 2} .0080091{col 40}{space 2} .0091168{col 51}{space 1}    0.88{col 60}{space 3}0.380{col 68}{space 4}-.0098596{col 81}{space 3} .0258778
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-9.96e-06{col 40}{space 2} 3.10e-06{col 51}{space 1}   -3.21{col 60}{space 3}0.001{col 68}{space 4} -.000016{col 81}{space 3}-3.88e-06
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.400781{col 40}{space 2} .0031855{col 51}{space 1}  753.65{col 60}{space 3}0.000{col 68}{space 4} 2.394538{col 81}{space 3} 2.407025
{txt}{space 20}Gender {c |}{col 28}{res}{space 2}-.0120389{col 40}{space 2} .0025788{col 51}{space 1}   -4.67{col 60}{space 3}0.000{col 68}{space 4}-.0170932{col 81}{space 3}-.0069846
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0704794{col 40}{space 2} .0025152{col 51}{space 1}  -28.02{col 60}{space 3}0.000{col 68}{space 4}-.0754091{col 81}{space 3}-.0655497
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0127811{col 40}{space 2} .0000951{col 51}{space 1} -134.39{col 60}{space 3}0.000{col 68}{space 4}-.0129675{col 81}{space 3}-.0125947
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0017679{col 40}{space 2} .0002985{col 51}{space 1}   -5.92{col 60}{space 3}0.000{col 68}{space 4}-.0023529{col 81}{space 3}-.0011829
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2} -.102249{col 40}{space 2} .0046319{col 51}{space 1}  -22.08{col 60}{space 3}0.000{col 68}{space 4}-.1113273{col 81}{space 3}-.0931707
{txt}{space 22}109  {c |}{col 28}{res}{space 2}-.2067031{col 40}{space 2}  .004702{col 51}{space 1}  -43.96{col 60}{space 3}0.000{col 68}{space 4}-.2159189{col 81}{space 3}-.1974874
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.2745339{col 40}{space 2} .0048617{col 51}{space 1}  -56.47{col 60}{space 3}0.000{col 68}{space 4}-.2840627{col 81}{space 3} -.265005
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .1119192{col 40}{space 2} .0049537{col 51}{space 1}   22.59{col 60}{space 3}0.000{col 68}{space 4} .1022101{col 81}{space 3} .1216283
{txt}{space 22}112  {c |}{col 28}{res}{space 2}-.8200824{col 40}{space 2} .0051901{col 51}{space 1} -158.01{col 60}{space 3}0.000{col 68}{space 4}-.8302548{col 81}{space 3}  -.80991
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6543244{col 40}{space 2} .0049762{col 51}{space 1} -131.49{col 60}{space 3}0.000{col 68}{space 4}-.6640775{col 81}{space 3}-.6445714
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.6614577{col 40}{space 2} .0052527{col 51}{space 1} -125.93{col 60}{space 3}0.000{col 68}{space 4}-.6717529{col 81}{space 3}-.6511625
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5141855{col 40}{space 2} .0054977{col 51}{space 1}  -93.53{col 60}{space 3}0.000{col 68}{space 4}-.5249607{col 81}{space 3}-.5034103
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4587401{col 40}{space 2} .0061006{col 51}{space 1}   75.20{col 60}{space 3}0.000{col 68}{space 4} .4467832{col 81}{space 3}  .470697
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87064.12{col 49}    21{col 58} 174170.2{col 69} 174382.1
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic5=s[1,5]
{txt}
{com}. di aic5-aic3
{res}5.6247489
{txt}
{com}. scalar aicc5=aic5+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C53=aicc5-aicc3
{txt}
{com}. *Change in AICc
. di C53
{res}5.6260326
{txt}
{com}. *Checking Conditional Significance of State x Age Interaction 
. *fracreg logit Agree c.Age##BirthState c.Age##c.BirthDistanceMiles RepState RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
. *margins, at(Age=(0 5 10 17 37) BirthState=(0 1)) atmeans level(84) post
. *Not statistically significant at any level of age
. 
. *Model 6
. fracreg logit Agree c.Age##i.BirthRegion c.Age##c.BirthDistanceMiles RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103496.92}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87588.615}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87065.711}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87063.748}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87063.748}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}20{txt}){col 67}= {res} 864364.69
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87063.748{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0019039{col 40}{space 2}  .000293{col 51}{space 1}   -6.50{col 60}{space 3}0.000{col 68}{space 4}-.0024782{col 81}{space 3}-.0013296
{txt}{space 13}1.BirthRegion {c |}{col 28}{res}{space 2} .0289626{col 40}{space 2} .0068784{col 51}{space 1}    4.21{col 60}{space 3}0.000{col 68}{space 4} .0154811{col 81}{space 3}  .042444
{txt}{space 26} {c |}
{space 9}BirthRegion#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0007458{col 40}{space 2} .0003679{col 51}{space 1}   -2.03{col 60}{space 3}0.043{col 68}{space 4}-.0014668{col 81}{space 3}-.0000247
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000281{col 40}{space 2} 4.22e-06{col 51}{space 1}   -6.67{col 60}{space 3}0.000{col 68}{space 4}-.0000364{col 81}{space 3}-.0000199
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 8.17e-07{col 40}{space 2} 2.16e-07{col 51}{space 1}    3.78{col 60}{space 3}0.000{col 68}{space 4} 3.94e-07{col 81}{space 3} 1.24e-06
{txt}{space 26} {c |}
{space 17}RepRegion {c |}{col 28}{res}{space 2}-.0036878{col 40}{space 2} .0052021{col 51}{space 1}   -0.71{col 60}{space 3}0.478{col 68}{space 4}-.0138837{col 81}{space 3} .0065081
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-.0000115{col 40}{space 2} 3.23e-06{col 51}{space 1}   -3.56{col 60}{space 3}0.000{col 68}{space 4}-.0000178{col 81}{space 3}-5.17e-06
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.400788{col 40}{space 2} .0031862{col 51}{space 1}  753.49{col 60}{space 3}0.000{col 68}{space 4} 2.394543{col 81}{space 3} 2.407033
{txt}{space 20}Gender {c |}{col 28}{res}{space 2} -.012667{col 40}{space 2} .0025725{col 51}{space 1}   -4.92{col 60}{space 3}0.000{col 68}{space 4} -.017709{col 81}{space 3} -.007625
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0697732{col 40}{space 2} .0025243{col 51}{space 1}  -27.64{col 60}{space 3}0.000{col 68}{space 4}-.0747208{col 81}{space 3}-.0648256
{txt}{space 21}DPres {c |}{col 28}{res}{space 2} -.012774{col 40}{space 2} .0000951{col 51}{space 1} -134.34{col 60}{space 3}0.000{col 68}{space 4}-.0129604{col 81}{space 3}-.0125877
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0017454{col 40}{space 2} .0002985{col 51}{space 1}   -5.85{col 60}{space 3}0.000{col 68}{space 4}-.0023305{col 81}{space 3}-.0011603
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1023276{col 40}{space 2}  .004632{col 51}{space 1}  -22.09{col 60}{space 3}0.000{col 68}{space 4}-.1114061{col 81}{space 3}-.0932491
{txt}{space 22}109  {c |}{col 28}{res}{space 2}-.2067437{col 40}{space 2} .0047026{col 51}{space 1}  -43.96{col 60}{space 3}0.000{col 68}{space 4}-.2159606{col 81}{space 3}-.1975268
{txt}{space 22}110  {c |}{col 28}{res}{space 2}-.2746028{col 40}{space 2} .0048625{col 51}{space 1}  -56.47{col 60}{space 3}0.000{col 68}{space 4} -.284133{col 81}{space 3}-.2650725
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .1118183{col 40}{space 2} .0049531{col 51}{space 1}   22.58{col 60}{space 3}0.000{col 68}{space 4} .1021103{col 81}{space 3} .1215263
{txt}{space 22}112  {c |}{col 28}{res}{space 2} -.820243{col 40}{space 2} .0051888{col 51}{space 1} -158.08{col 60}{space 3}0.000{col 68}{space 4}-.8304129{col 81}{space 3}-.8100731
{txt}{space 22}113  {c |}{col 28}{res}{space 2}-.6544146{col 40}{space 2} .0049744{col 51}{space 1} -131.56{col 60}{space 3}0.000{col 68}{space 4}-.6641642{col 81}{space 3} -.644665
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.6615512{col 40}{space 2} .0052514{col 51}{space 1} -125.98{col 60}{space 3}0.000{col 68}{space 4}-.6718438{col 81}{space 3}-.6512586
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5142316{col 40}{space 2} .0054986{col 51}{space 1}  -93.52{col 60}{space 3}0.000{col 68}{space 4}-.5250086{col 81}{space 3}-.5034546
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4495354{col 40}{space 2} .0064249{col 51}{space 1}   69.97{col 60}{space 3}0.000{col 68}{space 4} .4369428{col 81}{space 3} .4621279
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87063.75{col 49}    21{col 58} 174169.5{col 69} 174381.3
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic6=s[1,5]
{txt}
{com}. di aic6-aic3
{res}4.8771061
{txt}
{com}. scalar aicc6=aic6+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C63=aicc6-aicc3
{txt}
{com}. *Change in AICc
. di C63
{res}4.8783899
{txt}
{com}. 
. *Model 7
. fracreg logit Agree c.Age##i.BirthState c.Age##i.BirthRegion c.Age##c.BirthDistanceMiles RepState RepRegion RepDistanceMiles Party Gender Race DPres ChamSeniority i.congress, vce(robust)
{txt}note: Age omitted because of collinearity
note: Age omitted because of collinearity

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-103496.87}  
Iteration 1:{space 3}log pseudolikelihood = {res:-87588.482}  
Iteration 2:{space 3}log pseudolikelihood = {res:-87065.568}  
Iteration 3:{space 3}log pseudolikelihood = {res:-87063.605}  
Iteration 4:{space 3}log pseudolikelihood = {res:-87063.605}  
{res}
{txt}Fractional logistic regression{col 49}Number of obs{col 67}= {res}   177,629
{txt}{col 49}Wald chi2({res}23{txt}){col 67}= {res} 865981.26
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-87063.605{txt}{col 49}Pseudo R2{col 67}= {res}    0.2281

{txt}{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}                     Agree{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      z{col 60}   P>|z|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 23}Age {c |}{col 28}{res}{space 2}-.0019639{col 40}{space 2} .0002939{col 51}{space 1}   -6.68{col 60}{space 3}0.000{col 68}{space 4}  -.00254{col 81}{space 3}-.0013878
{txt}{space 14}1.BirthState {c |}{col 28}{res}{space 2}-.0240942{col 40}{space 2} .0134283{col 51}{space 1}   -1.79{col 60}{space 3}0.073{col 68}{space 4}-.0504132{col 81}{space 3} .0022248
{txt}{space 26} {c |}
{space 10}BirthState#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2} .0016262{col 40}{space 2} .0007126{col 51}{space 1}    2.28{col 60}{space 3}0.022{col 68}{space 4} .0002295{col 81}{space 3} .0030229
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 13}1.BirthRegion {c |}{col 28}{res}{space 2} .0348773{col 40}{space 2} .0074265{col 51}{space 1}    4.70{col 60}{space 3}0.000{col 68}{space 4} .0203216{col 81}{space 3}  .049433
{txt}{space 26} {c |}
{space 9}BirthRegion#c.Age {c |}
{space 24}1  {c |}{col 28}{res}{space 2}-.0011276{col 40}{space 2} .0003982{col 51}{space 1}   -2.83{col 60}{space 3}0.005{col 68}{space 4} -.001908{col 81}{space 3}-.0003472
{txt}{space 26} {c |}
{space 23}Age {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 8}BirthDistanceMiles {c |}{col 28}{res}{space 2}-.0000293{col 40}{space 2} 4.24e-06{col 51}{space 1}   -6.90{col 60}{space 3}0.000{col 68}{space 4}-.0000376{col 81}{space 3}-.0000209
{txt}{space 26} {c |}
c.Age#c.BirthDistanceMiles {c |}{col 28}{res}{space 2} 8.70e-07{col 40}{space 2} 2.17e-07{col 51}{space 1}    4.01{col 60}{space 3}0.000{col 68}{space 4} 4.45e-07{col 81}{space 3} 1.30e-06
{txt}{space 26} {c |}
{space 18}RepState {c |}{col 28}{res}{space 2} .0123509{col 40}{space 2} .0099456{col 51}{space 1}    1.24{col 60}{space 3}0.214{col 68}{space 4} -.007142{col 81}{space 3} .0318439
{txt}{space 17}RepRegion {c |}{col 28}{res}{space 2}-.0068169{col 40}{space 2} .0056673{col 51}{space 1}   -1.20{col 60}{space 3}0.229{col 68}{space 4}-.0179246{col 81}{space 3} .0042908
{txt}{space 10}RepDistanceMiles {c |}{col 28}{res}{space 2}-.0000108{col 40}{space 2} 3.26e-06{col 51}{space 1}   -3.30{col 60}{space 3}0.001{col 68}{space 4}-.0000171{col 81}{space 3}-4.36e-06
{txt}{space 21}Party {c |}{col 28}{res}{space 2} 2.400801{col 40}{space 2} .0031854{col 51}{space 1}  753.68{col 60}{space 3}0.000{col 68}{space 4} 2.394557{col 81}{space 3} 2.407044
{txt}{space 20}Gender {c |}{col 28}{res}{space 2}-.0123639{col 40}{space 2} .0025798{col 51}{space 1}   -4.79{col 60}{space 3}0.000{col 68}{space 4}-.0174203{col 81}{space 3}-.0073075
{txt}{space 22}Race {c |}{col 28}{res}{space 2}-.0696493{col 40}{space 2} .0025249{col 51}{space 1}  -27.58{col 60}{space 3}0.000{col 68}{space 4}-.0745981{col 81}{space 3}-.0647005
{txt}{space 21}DPres {c |}{col 28}{res}{space 2}-.0127717{col 40}{space 2} .0000951{col 51}{space 1} -134.24{col 60}{space 3}0.000{col 68}{space 4}-.0129582{col 81}{space 3}-.0125852
{txt}{space 13}ChamSeniority {c |}{col 28}{res}{space 2}-.0017529{col 40}{space 2} .0002985{col 51}{space 1}   -5.87{col 60}{space 3}0.000{col 68}{space 4}-.0023379{col 81}{space 3}-.0011679
{txt}{space 26} {c |}
{space 18}congress {c |}
{space 22}108  {c |}{col 28}{res}{space 2}-.1023497{col 40}{space 2} .0046321{col 51}{space 1}  -22.10{col 60}{space 3}0.000{col 68}{space 4}-.1114285{col 81}{space 3}-.0932709
{txt}{space 22}109  {c |}{col 28}{res}{space 2}-.2067759{col 40}{space 2} .0047026{col 51}{space 1}  -43.97{col 60}{space 3}0.000{col 68}{space 4}-.2159929{col 81}{space 3}-.1975589
{txt}{space 22}110  {c |}{col 28}{res}{space 2} -.274606{col 40}{space 2} .0048628{col 51}{space 1}  -56.47{col 60}{space 3}0.000{col 68}{space 4}-.2841368{col 81}{space 3}-.2650751
{txt}{space 22}111  {c |}{col 28}{res}{space 2} .1117638{col 40}{space 2} .0049536{col 51}{space 1}   22.56{col 60}{space 3}0.000{col 68}{space 4}  .102055{col 81}{space 3} .1214727
{txt}{space 22}112  {c |}{col 28}{res}{space 2}-.8202813{col 40}{space 2} .0051889{col 51}{space 1} -158.08{col 60}{space 3}0.000{col 68}{space 4}-.8304513{col 81}{space 3}-.8101112
{txt}{space 22}113  {c |}{col 28}{res}{space 2} -.654466{col 40}{space 2} .0049752{col 51}{space 1} -131.55{col 60}{space 3}0.000{col 68}{space 4}-.6642172{col 81}{space 3}-.6447147
{txt}{space 22}114  {c |}{col 28}{res}{space 2}-.6615749{col 40}{space 2} .0052523{col 51}{space 1} -125.96{col 60}{space 3}0.000{col 68}{space 4}-.6718692{col 81}{space 3}-.6512806
{txt}{space 22}115  {c |}{col 28}{res}{space 2}-.5142504{col 40}{space 2}  .005498{col 51}{space 1}  -93.53{col 60}{space 3}0.000{col 68}{space 4}-.5250263{col 81}{space 3}-.5034745
{txt}{space 26} {c |}
{space 21}_cons {c |}{col 28}{res}{space 2} .4496356{col 40}{space 2} .0064363{col 51}{space 1}   69.86{col 60}{space 3}0.000{col 68}{space 4} .4370207{col 81}{space 3} .4622505
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. estat ic

Akaike's information criterion and Bayesian information criterion

{txt}{hline 13}{c TT}{hline 63}
       Model {c |}        Obs  ll(null)  ll(model)      df         AIC        BIC
{hline 13}{c +}{hline 63}
{ralign 12:.}{col 14}{c |}{res}{col 16}   177,629{col 27}-112791.1{col 38}-87063.61{col 49}    24{col 58} 174175.2{col 69} 174417.3
{txt}{hline 13}{c BT}{hline 63}
{p 15 21 2}
Note: N=Obs used in calculating BIC; see {helpb bic_note:[R] BIC note}.
{p_end}

{com}. mat s=r(S)
{txt}
{com}. scalar aic7=s[1,5]
{txt}
{com}. di aic7-aic3
{res}10.591735
{txt}
{com}. scalar aicc7=aic7+(2*e(df_m)*(e(df_m)+1))/(e(N)-e(df_m)-1)
{txt}
{com}. scalar C73=aicc7-aicc3
{txt}
{com}. *Change in AICc
. di C73
{res}10.594506
{txt}
{com}. 
. *Calculating w_i (i.e., Probability of best model)
. scalar E1=exp(-.5*C13)
{txt}
{com}. scalar E2=exp(-.5*C23)
{txt}
{com}. scalar E3=exp(-.5*C33)
{txt}
{com}. scalar E4=exp(-.5*C43)
{txt}
{com}. scalar E5=exp(-.5*C53)
{txt}
{com}. scalar E6=exp(-.5*C63)
{txt}
{com}. scalar E7=exp(-.5*C73)
{txt}
{com}. 
. scalar W1=(E1)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W2=(E2)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W3=(E3)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W4=(E4)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W5=(E5)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W6=(E6)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. scalar W7=(E7)/(E1+E2+E3+E4+E5+E6+E7)
{txt}
{com}. 
. di W1
{res}.00203666
{txt}
{com}. di W2
{res}.01586486
{txt}
{com}. di W3
{res}.85149368
{txt}
{com}. di W4
{res}.00095633
{txt}
{com}. di W5
{res}.05110977
{txt}
{com}. di W6
{res}.07427669
{txt}
{com}. di W7
{res}.004262
{txt}
{com}. 
. clear
{txt}
{com}. 
. 
. *****************************************
. *Agriculture Protection Models - Table 5
. *****************************************
. 
. *Friend of the Farm Bureau Models
. 
. *Select directory
. use "AgricultureData_AgBirth.dta"
{txt}
{com}. 
. *Column 1
. regress friend career prop_ag ln_ag_pac dist_povertypct dist_mednhhincome house_ag rep ideology female age state_fe_* cong_* if chamber_2==0, vce(cluster icpsr_id)
{txt}note: state_fe_1 omitted because of collinearity
note: state_fe_11 omitted because of collinearity
note: state_fe_50 omitted because of collinearity
note: cong_1 omitted because of collinearity

Linear regression                               Number of obs     = {res}     2,159
                                                {txt}{help j_robustsingular:F(58, 641) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3814
                                                {txt}Root MSE          =    {res} .39867

{txt}{ralign 83:(Std. Err. adjusted for {res:642} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}           friend{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}career {c |}{col 19}{res}{space 2} .1835692{col 31}{space 2} .0998842{col 42}{space 1}    1.84{col 51}{space 3}0.067{col 59}{space 4}-.0125705{col 72}{space 3} .3797089
{txt}{space 10}prop_ag {c |}{col 19}{res}{space 2} 2.393791{col 31}{space 2} .7730339{col 42}{space 1}    3.10{col 51}{space 3}0.002{col 59}{space 4} .8758067{col 72}{space 3} 3.911776
{txt}{space 8}ln_ag_pac {c |}{col 19}{res}{space 2} .0170787{col 31}{space 2} .0037971{col 42}{space 1}    4.50{col 51}{space 3}0.000{col 59}{space 4} .0096225{col 72}{space 3} .0245349
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2}-.8735031{col 31}{space 2} .3661862{col 42}{space 1}   -2.39{col 51}{space 3}0.017{col 59}{space 4}-1.592573{col 72}{space 3}-.1544337
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0054893{col 31}{space 2} .0019332{col 42}{space 1}   -2.84{col 51}{space 3}0.005{col 59}{space 4}-.0092854{col 72}{space 3}-.0016931
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0876752{col 31}{space 2} .0346955{col 42}{space 1}    2.53{col 51}{space 3}0.012{col 59}{space 4} .0195447{col 72}{space 3} .1558057
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2} .3784941{col 31}{space 2} .0290023{col 42}{space 1}   13.05{col 51}{space 3}0.000{col 59}{space 4} .3215431{col 72}{space 3} .4354451
{txt}{space 9}ideology {c |}{col 19}{res}{space 2} -.123689{col 31}{space 2} .1934556{col 42}{space 1}   -0.64{col 51}{space 3}0.523{col 59}{space 4}-.5035723{col 72}{space 3} .2561943
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0136382{col 31}{space 2}  .025399{col 42}{space 1}   -0.54{col 51}{space 3}0.591{col 59}{space 4}-.0635135{col 72}{space 3} .0362371
{txt}{space 14}age {c |}{col 19}{res}{space 2}-.0005078{col 31}{space 2} .0009847{col 42}{space 1}   -0.52{col 51}{space 3}0.606{col 59}{space 4}-.0024415{col 72}{space 3} .0014258
{txt}{space 7}state_fe_1 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 7}state_fe_2 {c |}{col 19}{res}{space 2}-.0606686{col 31}{space 2} .1113781{col 42}{space 1}   -0.54{col 51}{space 3}0.586{col 59}{space 4}-.2793785{col 72}{space 3} .1580414
{txt}{space 7}state_fe_3 {c |}{col 19}{res}{space 2} .1937268{col 31}{space 2} .1152373{col 42}{space 1}    1.68{col 51}{space 3}0.093{col 59}{space 4}-.0325614{col 72}{space 3} .4200151
{txt}{space 7}state_fe_4 {c |}{col 19}{res}{space 2}-.0075383{col 31}{space 2} .0826657{col 42}{space 1}   -0.09{col 51}{space 3}0.927{col 59}{space 4}-.1698667{col 72}{space 3} .1547901
{txt}{space 7}state_fe_5 {c |}{col 19}{res}{space 2}-.2300061{col 31}{space 2} .0435368{col 42}{space 1}   -5.28{col 51}{space 3}0.000{col 59}{space 4} -.315498{col 72}{space 3}-.1445142
{txt}{space 7}state_fe_6 {c |}{col 19}{res}{space 2} -.138887{col 31}{space 2} .0726995{col 42}{space 1}   -1.91{col 51}{space 3}0.057{col 59}{space 4}-.2816449{col 72}{space 3}  .003871
{txt}{space 7}state_fe_7 {c |}{col 19}{res}{space 2}-.1551098{col 31}{space 2} .0953676{col 42}{space 1}   -1.63{col 51}{space 3}0.104{col 59}{space 4}-.3423805{col 72}{space 3} .0321609
{txt}{space 7}state_fe_8 {c |}{col 19}{res}{space 2}-.7064852{col 31}{space 2} .0386762{col 42}{space 1}  -18.27{col 51}{space 3}0.000{col 59}{space 4}-.7824325{col 72}{space 3}-.6305379
{txt}{space 7}state_fe_9 {c |}{col 19}{res}{space 2}-.2199967{col 31}{space 2}  .047988{col 42}{space 1}   -4.58{col 51}{space 3}0.000{col 59}{space 4}-.3142294{col 72}{space 3}-.1257641
{txt}{space 6}state_fe_10 {c |}{col 19}{res}{space 2}-.0300816{col 31}{space 2} .0629078{col 42}{space 1}   -0.48{col 51}{space 3}0.633{col 59}{space 4}-.1536119{col 72}{space 3} .0934487
{txt}{space 6}state_fe_11 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 6}state_fe_12 {c |}{col 19}{res}{space 2}-.0992559{col 31}{space 2} .0817656{col 42}{space 1}   -1.21{col 51}{space 3}0.225{col 59}{space 4}-.2598167{col 72}{space 3} .0613049
{txt}{space 6}state_fe_13 {c |}{col 19}{res}{space 2} .0254842{col 31}{space 2}  .113734{col 42}{space 1}    0.22{col 51}{space 3}0.823{col 59}{space 4} -.197852{col 72}{space 3} .2488204
{txt}{space 6}state_fe_14 {c |}{col 19}{res}{space 2}-.0050513{col 31}{space 2}  .061159{col 42}{space 1}   -0.08{col 51}{space 3}0.934{col 59}{space 4}-.1251475{col 72}{space 3} .1150448
{txt}{space 6}state_fe_15 {c |}{col 19}{res}{space 2} .0895372{col 31}{space 2} .0681204{col 42}{space 1}    1.31{col 51}{space 3}0.189{col 59}{space 4}-.0442288{col 72}{space 3} .2233032
{txt}{space 6}state_fe_16 {c |}{col 19}{res}{space 2} .0964811{col 31}{space 2} .0960635{col 42}{space 1}    1.00{col 51}{space 3}0.316{col 59}{space 4} -.092156{col 72}{space 3} .2851182
{txt}{space 6}state_fe_17 {c |}{col 19}{res}{space 2} .1400851{col 31}{space 2} .0700104{col 42}{space 1}    2.00{col 51}{space 3}0.046{col 59}{space 4} .0026076{col 72}{space 3} .2775625
{txt}{space 6}state_fe_18 {c |}{col 19}{res}{space 2} .2132445{col 31}{space 2} .0801311{col 42}{space 1}    2.66{col 51}{space 3}0.008{col 59}{space 4} .0558933{col 72}{space 3} .3705958
{txt}{space 6}state_fe_19 {c |}{col 19}{res}{space 2}-.2242232{col 31}{space 2} .0491456{col 42}{space 1}   -4.56{col 51}{space 3}0.000{col 59}{space 4}-.3207291{col 72}{space 3}-.1277173
{txt}{space 6}state_fe_20 {c |}{col 19}{res}{space 2}-.1345229{col 31}{space 2} .0774746{col 42}{space 1}   -1.74{col 51}{space 3}0.083{col 59}{space 4}-.2866576{col 72}{space 3} .0176117
{txt}{space 6}state_fe_21 {c |}{col 19}{res}{space 2} -.428572{col 31}{space 2} .0529872{col 42}{space 1}   -8.09{col 51}{space 3}0.000{col 59}{space 4}-.5326216{col 72}{space 3}-.3245224
{txt}{space 6}state_fe_22 {c |}{col 19}{res}{space 2}-.0216594{col 31}{space 2}  .061767{col 42}{space 1}   -0.35{col 51}{space 3}0.726{col 59}{space 4}-.1429494{col 72}{space 3} .0996307
{txt}{space 6}state_fe_23 {c |}{col 19}{res}{space 2}-.0984029{col 31}{space 2} .0927601{col 42}{space 1}   -1.06{col 51}{space 3}0.289{col 59}{space 4}-.2805532{col 72}{space 3} .0837474
{txt}{space 6}state_fe_24 {c |}{col 19}{res}{space 2} .0766027{col 31}{space 2} .0626139{col 42}{space 1}    1.22{col 51}{space 3}0.222{col 59}{space 4}-.0463504{col 72}{space 3} .1995559
{txt}{space 6}state_fe_25 {c |}{col 19}{res}{space 2} .0399127{col 31}{space 2} .0884472{col 42}{space 1}    0.45{col 51}{space 3}0.652{col 59}{space 4}-.1337686{col 72}{space 3}  .213594
{txt}{space 6}state_fe_26 {c |}{col 19}{res}{space 2} .0740326{col 31}{space 2} .0550314{col 42}{space 1}    1.35{col 51}{space 3}0.179{col 59}{space 4} -.034031{col 72}{space 3} .1820963
{txt}{space 6}state_fe_27 {c |}{col 19}{res}{space 2} .0614178{col 31}{space 2} .0491823{col 42}{space 1}    1.25{col 51}{space 3}0.212{col 59}{space 4}-.0351601{col 72}{space 3} .1579956
{txt}{space 6}state_fe_28 {c |}{col 19}{res}{space 2}-.5349369{col 31}{space 2} .0434212{col 42}{space 1}  -12.32{col 51}{space 3}0.000{col 59}{space 4}-.6202018{col 72}{space 3} -.449672
{txt}{space 6}state_fe_29 {c |}{col 19}{res}{space 2} .0312616{col 31}{space 2} .0480272{col 42}{space 1}    0.65{col 51}{space 3}0.515{col 59}{space 4}-.0630479{col 72}{space 3} .1255712
{txt}{space 6}state_fe_30 {c |}{col 19}{res}{space 2}-.5267972{col 31}{space 2} .0731347{col 42}{space 1}   -7.20{col 51}{space 3}0.000{col 59}{space 4}-.6704098{col 72}{space 3}-.3831846
{txt}{space 6}state_fe_31 {c |}{col 19}{res}{space 2}-.4034608{col 31}{space 2}  .069959{col 42}{space 1}   -5.77{col 51}{space 3}0.000{col 59}{space 4}-.5408372{col 72}{space 3}-.2660844
{txt}{space 6}state_fe_32 {c |}{col 19}{res}{space 2} .1284484{col 31}{space 2}  .092786{col 42}{space 1}    1.38{col 51}{space 3}0.167{col 59}{space 4}-.0537527{col 72}{space 3} .3106496
{txt}{space 6}state_fe_33 {c |}{col 19}{res}{space 2} .0441338{col 31}{space 2} .1255013{col 42}{space 1}    0.35{col 51}{space 3}0.725{col 59}{space 4}-.2023096{col 72}{space 3} .2905772
{txt}{space 6}state_fe_34 {c |}{col 19}{res}{space 2} .0256167{col 31}{space 2} .0478563{col 42}{space 1}    0.54{col 51}{space 3}0.593{col 59}{space 4}-.0683573{col 72}{space 3} .1195908
{txt}{space 6}state_fe_35 {c |}{col 19}{res}{space 2}-.0151281{col 31}{space 2} .0505449{col 42}{space 1}   -0.30{col 51}{space 3}0.765{col 59}{space 4}-.1143817{col 72}{space 3} .0841255
{txt}{space 6}state_fe_36 {c |}{col 19}{res}{space 2} .2240822{col 31}{space 2} .0643782{col 42}{space 1}    3.48{col 51}{space 3}0.001{col 59}{space 4} .0976645{col 72}{space 3} .3504999
{txt}{space 6}state_fe_37 {c |}{col 19}{res}{space 2}-.2208995{col 31}{space 2} .0936083{col 42}{space 1}   -2.36{col 51}{space 3}0.019{col 59}{space 4}-.4047154{col 72}{space 3}-.0370835
{txt}{space 6}state_fe_38 {c |}{col 19}{res}{space 2}  .093715{col 31}{space 2}  .051588{col 42}{space 1}    1.82{col 51}{space 3}0.070{col 59}{space 4}-.0075868{col 72}{space 3} .1950169
{txt}{space 6}state_fe_39 {c |}{col 19}{res}{space 2}-.2952502{col 31}{space 2} .0506627{col 42}{space 1}   -5.83{col 51}{space 3}0.000{col 59}{space 4}-.3947351{col 72}{space 3}-.1957652
{txt}{space 6}state_fe_40 {c |}{col 19}{res}{space 2}-.1613134{col 31}{space 2} .0892952{col 42}{space 1}   -1.81{col 51}{space 3}0.071{col 59}{space 4}-.3366598{col 72}{space 3}  .014033
{txt}{space 6}state_fe_41 {c |}{col 19}{res}{space 2}-.0490369{col 31}{space 2} .1770805{col 42}{space 1}   -0.28{col 51}{space 3}0.782{col 59}{space 4} -.396765{col 72}{space 3} .2986911
{txt}{space 6}state_fe_42 {c |}{col 19}{res}{space 2} .1172487{col 31}{space 2} .0956504{col 42}{space 1}    1.23{col 51}{space 3}0.221{col 59}{space 4}-.0705773{col 72}{space 3} .3050747
{txt}{space 6}state_fe_43 {c |}{col 19}{res}{space 2} .1066901{col 31}{space 2} .0473023{col 42}{space 1}    2.26{col 51}{space 3}0.024{col 59}{space 4}  .013804{col 72}{space 3} .1995762
{txt}{space 6}state_fe_44 {c |}{col 19}{res}{space 2} .0214802{col 31}{space 2} .1242594{col 42}{space 1}    0.17{col 51}{space 3}0.863{col 59}{space 4}-.2225245{col 72}{space 3} .2654849
{txt}{space 6}state_fe_45 {c |}{col 19}{res}{space 2}-.1360786{col 31}{space 2} .0670307{col 42}{space 1}   -2.03{col 51}{space 3}0.043{col 59}{space 4}-.2677049{col 72}{space 3}-.0044522
{txt}{space 6}state_fe_46 {c |}{col 19}{res}{space 2}-.0820766{col 31}{space 2} .1954068{col 42}{space 1}   -0.42{col 51}{space 3}0.675{col 59}{space 4}-.4657914{col 72}{space 3} .3016382
{txt}{space 6}state_fe_47 {c |}{col 19}{res}{space 2}-.1903518{col 31}{space 2} .0616349{col 42}{space 1}   -3.09{col 51}{space 3}0.002{col 59}{space 4}-.3113825{col 72}{space 3}-.0693211
{txt}{space 6}state_fe_48 {c |}{col 19}{res}{space 2}-.1658985{col 31}{space 2} .0718085{col 42}{space 1}   -2.31{col 51}{space 3}0.021{col 59}{space 4}-.3069069{col 72}{space 3}-.0248901
{txt}{space 6}state_fe_49 {c |}{col 19}{res}{space 2}-.2650507{col 31}{space 2} .0869547{col 42}{space 1}   -3.05{col 51}{space 3}0.002{col 59}{space 4}-.4358012{col 72}{space 3}-.0943002
{txt}{space 6}state_fe_50 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 11}cong_1 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 11}cong_2 {c |}{col 19}{res}{space 2} .0000302{col 31}{space 2} .0248496{col 42}{space 1}    0.00{col 51}{space 3}0.999{col 59}{space 4}-.0487663{col 72}{space 3} .0488267
{txt}{space 11}cong_3 {c |}{col 19}{res}{space 2} .0142416{col 31}{space 2}  .024449{col 42}{space 1}    0.58{col 51}{space 3}0.560{col 59}{space 4}-.0337682{col 72}{space 3} .0622514
{txt}{space 11}cong_4 {c |}{col 19}{res}{space 2} .0387919{col 31}{space 2} .0234364{col 42}{space 1}    1.66{col 51}{space 3}0.098{col 59}{space 4}-.0072294{col 72}{space 3} .0848132
{txt}{space 11}cong_5 {c |}{col 19}{res}{space 2} .0827378{col 31}{space 2} .0321641{col 42}{space 1}    2.57{col 51}{space 3}0.010{col 59}{space 4} .0195781{col 72}{space 3} .1458974
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7005818{col 31}{space 2} .1454705{col 42}{space 1}    4.82{col 51}{space 3}0.000{col 59}{space 4} .4149255{col 72}{space 3} .9862381
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Column 2 
. *Normalized (to unit interval) croplandharvested_acres
. sum croplandharvested_acres

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
croplandha~s {c |}{res}      1,780    74119.51    91565.12          0     600848
{txt}
{com}. return list

{txt}scalars:
                  r(N) =  {res}1780
              {txt}r(sum_w) =  {res}1780
               {txt}r(mean) =  {res}74119.5106741573
                {txt}r(Var) =  {res}8384170826.656997
                 {txt}r(sd) =  {res}91565.1179579702
                {txt}r(min) =  {res}0
                {txt}r(max) =  {res}600848
                {txt}r(sum) =  {res}131932729
{txt}
{com}. gen cropmean=r(mean)
{txt}
{com}. gen cropsd=r(sd)
{txt}
{com}. gen cropmax=r(max)
{txt}
{com}. gen cropmin=0
{txt}
{com}. gen crop_Unit=1/cropmax*(croplandharvested_acres-cropmax)+1
{txt}(379 missing values generated)

{com}. 
. regress friend crop_Unit career prop_ag ln_ag_pac dist_povertypct dist_mednhhincome house_ag rep ideology female age state_fe_* cong_* if chamber_2==0, vce(cluster icpsr_id)
{txt}note: state_fe_1 omitted because of collinearity
note: state_fe_11 omitted because of collinearity
note: state_fe_26 omitted because of collinearity
note: state_fe_28 omitted because of collinearity
note: state_fe_41 omitted because of collinearity
note: cong_4 omitted because of collinearity

Linear regression                               Number of obs     = {res}     1,780
                                                {txt}{help j_robustsingular:F(56, 502) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3941
                                                {txt}Root MSE          =    {res} .39564

{txt}{ralign 83:(Std. Err. adjusted for {res:503} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}           friend{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .2060763{col 31}{space 2} .0902256{col 42}{space 1}    2.28{col 51}{space 3}0.023{col 59}{space 4} .0288099{col 72}{space 3} .3833427
{txt}{space 11}career {c |}{col 19}{res}{space 2}  .207766{col 31}{space 2} .1160785{col 42}{space 1}    1.79{col 51}{space 3}0.074{col 59}{space 4}-.0202934{col 72}{space 3} .4358255
{txt}{space 10}prop_ag {c |}{col 19}{res}{space 2} 1.764308{col 31}{space 2} .9012808{col 42}{space 1}    1.96{col 51}{space 3}0.051{col 59}{space 4}-.0064392{col 72}{space 3} 3.535055
{txt}{space 8}ln_ag_pac {c |}{col 19}{res}{space 2} .0165344{col 31}{space 2} .0042064{col 42}{space 1}    3.93{col 51}{space 3}0.000{col 59}{space 4} .0082701{col 72}{space 3} .0247987
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2}-.8645831{col 31}{space 2} .3983523{col 42}{space 1}   -2.17{col 51}{space 3}0.030{col 59}{space 4}-1.647226{col 72}{space 3}  -.08194
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0044552{col 31}{space 2}   .00199{col 42}{space 1}   -2.24{col 51}{space 3}0.026{col 59}{space 4} -.008365{col 72}{space 3}-.0005454
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0772399{col 31}{space 2} .0384387{col 42}{space 1}    2.01{col 51}{space 3}0.045{col 59}{space 4} .0017194{col 72}{space 3} .1527604
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2} .3901158{col 31}{space 2} .0315394{col 42}{space 1}   12.37{col 51}{space 3}0.000{col 59}{space 4} .3281504{col 72}{space 3} .4520813
{txt}{space 9}ideology {c |}{col 19}{res}{space 2}-.0998257{col 31}{space 2} .1929941{col 42}{space 1}   -0.52{col 51}{space 3}0.605{col 59}{space 4}-.4790014{col 72}{space 3} .2793499
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0293045{col 31}{space 2} .0255267{col 42}{space 1}   -1.15{col 51}{space 3}0.252{col 59}{space 4}-.0794569{col 72}{space 3}  .020848
{txt}{space 14}age {c |}{col 19}{res}{space 2} .0001318{col 31}{space 2} .0010169{col 42}{space 1}    0.13{col 51}{space 3}0.897{col 59}{space 4} -.001866{col 72}{space 3} .0021297
{txt}{space 7}state_fe_1 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 7}state_fe_2 {c |}{col 19}{res}{space 2} .8209135{col 31}{space 2} .1050017{col 42}{space 1}    7.82{col 51}{space 3}0.000{col 59}{space 4} .6146167{col 72}{space 3}  1.02721
{txt}{space 7}state_fe_3 {c |}{col 19}{res}{space 2} 1.042661{col 31}{space 2} .1599816{col 42}{space 1}    6.52{col 51}{space 3}0.000{col 59}{space 4} .7283448{col 72}{space 3} 1.356977
{txt}{space 7}state_fe_4 {c |}{col 19}{res}{space 2} .8679856{col 31}{space 2} .0873789{col 42}{space 1}    9.93{col 51}{space 3}0.000{col 59}{space 4} .6963121{col 72}{space 3} 1.039659
{txt}{space 7}state_fe_5 {c |}{col 19}{res}{space 2} .6221577{col 31}{space 2} .0564716{col 42}{space 1}   11.02{col 51}{space 3}0.000{col 59}{space 4}  .511208{col 72}{space 3} .7331074
{txt}{space 7}state_fe_6 {c |}{col 19}{res}{space 2} .7422473{col 31}{space 2} .0811194{col 42}{space 1}    9.15{col 51}{space 3}0.000{col 59}{space 4} .5828719{col 72}{space 3} .9016227
{txt}{space 7}state_fe_7 {c |}{col 19}{res}{space 2} .7033776{col 31}{space 2} .1304305{col 42}{space 1}    5.39{col 51}{space 3}0.000{col 59}{space 4} .4471207{col 72}{space 3} .9596345
{txt}{space 7}state_fe_8 {c |}{col 19}{res}{space 2} .1415124{col 31}{space 2} .0433201{col 42}{space 1}    3.27{col 51}{space 3}0.001{col 59}{space 4} .0564014{col 72}{space 3} .2266234
{txt}{space 7}state_fe_9 {c |}{col 19}{res}{space 2} .6164591{col 31}{space 2} .0621824{col 42}{space 1}    9.91{col 51}{space 3}0.000{col 59}{space 4} .4942892{col 72}{space 3}  .738629
{txt}{space 6}state_fe_10 {c |}{col 19}{res}{space 2} .8393691{col 31}{space 2} .0765589{col 42}{space 1}   10.96{col 51}{space 3}0.000{col 59}{space 4} .6889537{col 72}{space 3} .9897845
{txt}{space 6}state_fe_11 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 6}state_fe_12 {c |}{col 19}{res}{space 2}  .692312{col 31}{space 2} .0994194{col 42}{space 1}    6.96{col 51}{space 3}0.000{col 59}{space 4} .4969827{col 72}{space 3} .8876413
{txt}{space 6}state_fe_13 {c |}{col 19}{res}{space 2} .9701167{col 31}{space 2} .0466163{col 42}{space 1}   20.81{col 51}{space 3}0.000{col 59}{space 4} .8785295{col 72}{space 3} 1.061704
{txt}{space 6}state_fe_14 {c |}{col 19}{res}{space 2} .8393794{col 31}{space 2}   .07013{col 42}{space 1}   11.97{col 51}{space 3}0.000{col 59}{space 4} .7015949{col 72}{space 3} .9771638
{txt}{space 6}state_fe_15 {c |}{col 19}{res}{space 2}  .912666{col 31}{space 2} .0632573{col 42}{space 1}   14.43{col 51}{space 3}0.000{col 59}{space 4} .7883843{col 72}{space 3} 1.036948
{txt}{space 6}state_fe_16 {c |}{col 19}{res}{space 2} .8585248{col 31}{space 2} .1594878{col 42}{space 1}    5.38{col 51}{space 3}0.000{col 59}{space 4}  .545179{col 72}{space 3} 1.171871
{txt}{space 6}state_fe_17 {c |}{col 19}{res}{space 2} 1.059154{col 31}{space 2} .0745207{col 42}{space 1}   14.21{col 51}{space 3}0.000{col 59}{space 4} .9127428{col 72}{space 3} 1.205565
{txt}{space 6}state_fe_18 {c |}{col 19}{res}{space 2} 1.023004{col 31}{space 2} .0809135{col 42}{space 1}   12.64{col 51}{space 3}0.000{col 59}{space 4} .8640332{col 72}{space 3} 1.181975
{txt}{space 6}state_fe_19 {c |}{col 19}{res}{space 2} .6472532{col 31}{space 2}  .056723{col 42}{space 1}   11.41{col 51}{space 3}0.000{col 59}{space 4} .5358094{col 72}{space 3} .7586969
{txt}{space 6}state_fe_20 {c |}{col 19}{res}{space 2} .6497596{col 31}{space 2} .0983293{col 42}{space 1}    6.61{col 51}{space 3}0.000{col 59}{space 4}  .456572{col 72}{space 3} .8429472
{txt}{space 6}state_fe_21 {c |}{col 19}{res}{space 2} .4675919{col 31}{space 2}  .059037{col 42}{space 1}    7.92{col 51}{space 3}0.000{col 59}{space 4} .3516019{col 72}{space 3}  .583582
{txt}{space 6}state_fe_22 {c |}{col 19}{res}{space 2} .8266446{col 31}{space 2} .0692736{col 42}{space 1}   11.93{col 51}{space 3}0.000{col 59}{space 4} .6905427{col 72}{space 3} .9627465
{txt}{space 6}state_fe_23 {c |}{col 19}{res}{space 2} .8045719{col 31}{space 2} .1650682{col 42}{space 1}    4.87{col 51}{space 3}0.000{col 59}{space 4} .4802623{col 72}{space 3} 1.128881
{txt}{space 6}state_fe_24 {c |}{col 19}{res}{space 2} .9686108{col 31}{space 2} .0708928{col 42}{space 1}   13.66{col 51}{space 3}0.000{col 59}{space 4} .8293277{col 72}{space 3} 1.107894
{txt}{space 6}state_fe_25 {c |}{col 19}{res}{space 2} .9411461{col 31}{space 2} .0928581{col 42}{space 1}   10.14{col 51}{space 3}0.000{col 59}{space 4} .7587077{col 72}{space 3} 1.123584
{txt}{space 6}state_fe_26 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 6}state_fe_27 {c |}{col 19}{res}{space 2} .9245583{col 31}{space 2} .0539922{col 42}{space 1}   17.12{col 51}{space 3}0.000{col 59}{space 4} .8184798{col 72}{space 3} 1.030637
{txt}{space 6}state_fe_28 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 6}state_fe_29 {c |}{col 19}{res}{space 2} .8658223{col 31}{space 2} .0635218{col 42}{space 1}   13.63{col 51}{space 3}0.000{col 59}{space 4} .7410209{col 72}{space 3} .9906237
{txt}{space 6}state_fe_30 {c |}{col 19}{res}{space 2} .3546844{col 31}{space 2} .0825597{col 42}{space 1}    4.30{col 51}{space 3}0.000{col 59}{space 4} .1924793{col 72}{space 3} .5168896
{txt}{space 6}state_fe_31 {c |}{col 19}{res}{space 2} .4649044{col 31}{space 2}  .077952{col 42}{space 1}    5.96{col 51}{space 3}0.000{col 59}{space 4} .3117521{col 72}{space 3} .6180568
{txt}{space 6}state_fe_32 {c |}{col 19}{res}{space 2} 1.004502{col 31}{space 2} .1036071{col 42}{space 1}    9.70{col 51}{space 3}0.000{col 59}{space 4} .8009452{col 72}{space 3} 1.208059
{txt}{space 6}state_fe_33 {c |}{col 19}{res}{space 2} .9089528{col 31}{space 2}  .120405{col 42}{space 1}    7.55{col 51}{space 3}0.000{col 59}{space 4}  .672393{col 72}{space 3} 1.145513
{txt}{space 6}state_fe_34 {c |}{col 19}{res}{space 2} .9087963{col 31}{space 2} .0578358{col 42}{space 1}   15.71{col 51}{space 3}0.000{col 59}{space 4} .7951663{col 72}{space 3} 1.022426
{txt}{space 6}state_fe_35 {c |}{col 19}{res}{space 2} .8493808{col 31}{space 2}  .056593{col 42}{space 1}   15.01{col 51}{space 3}0.000{col 59}{space 4} .7381924{col 72}{space 3} .9605692
{txt}{space 6}state_fe_36 {c |}{col 19}{res}{space 2} 1.118144{col 31}{space 2} .0976871{col 42}{space 1}   11.45{col 51}{space 3}0.000{col 59}{space 4} .9262179{col 72}{space 3}  1.31007
{txt}{space 6}state_fe_37 {c |}{col 19}{res}{space 2} .6988449{col 31}{space 2} .1424232{col 42}{space 1}    4.91{col 51}{space 3}0.000{col 59}{space 4} .4190258{col 72}{space 3} .9786639
{txt}{space 6}state_fe_38 {c |}{col 19}{res}{space 2} .9822476{col 31}{space 2} .0583499{col 42}{space 1}   16.83{col 51}{space 3}0.000{col 59}{space 4} .8676075{col 72}{space 3} 1.096888
{txt}{space 6}state_fe_39 {c |}{col 19}{res}{space 2} .6001722{col 31}{space 2} .0649009{col 42}{space 1}    9.25{col 51}{space 3}0.000{col 59}{space 4} .4726614{col 72}{space 3}  .727683
{txt}{space 6}state_fe_40 {c |}{col 19}{res}{space 2} .7111411{col 31}{space 2} .0959604{col 42}{space 1}    7.41{col 51}{space 3}0.000{col 59}{space 4} .5226077{col 72}{space 3} .8996745
{txt}{space 6}state_fe_41 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 6}state_fe_42 {c |}{col 19}{res}{space 2} .9922035{col 31}{space 2} .1026352{col 42}{space 1}    9.67{col 51}{space 3}0.000{col 59}{space 4}  .790556{col 72}{space 3} 1.193851
{txt}{space 6}state_fe_43 {c |}{col 19}{res}{space 2}  .974865{col 31}{space 2} .0689756{col 42}{space 1}   14.13{col 51}{space 3}0.000{col 59}{space 4} .8393486{col 72}{space 3} 1.110381
{txt}{space 6}state_fe_44 {c |}{col 19}{res}{space 2} .7710093{col 31}{space 2} .0503931{col 42}{space 1}   15.30{col 51}{space 3}0.000{col 59}{space 4} .6720019{col 72}{space 3} .8700167
{txt}{space 6}state_fe_45 {c |}{col 19}{res}{space 2} .6778746{col 31}{space 2} .0727464{col 42}{space 1}    9.32{col 51}{space 3}0.000{col 59}{space 4} .5349496{col 72}{space 3} .8207996
{txt}{space 6}state_fe_46 {c |}{col 19}{res}{space 2} .8103606{col 31}{space 2} .2023013{col 42}{space 1}    4.01{col 51}{space 3}0.000{col 59}{space 4}  .412899{col 72}{space 3} 1.207822
{txt}{space 6}state_fe_47 {c |}{col 19}{res}{space 2} .6528282{col 31}{space 2} .0707481{col 42}{space 1}    9.23{col 51}{space 3}0.000{col 59}{space 4} .5138294{col 72}{space 3}  .791827
{txt}{space 6}state_fe_48 {c |}{col 19}{res}{space 2} .6874314{col 31}{space 2} .0839115{col 42}{space 1}    8.19{col 51}{space 3}0.000{col 59}{space 4} .5225705{col 72}{space 3} .8522924
{txt}{space 6}state_fe_49 {c |}{col 19}{res}{space 2}  .643517{col 31}{space 2} .0992659{col 42}{space 1}    6.48{col 51}{space 3}0.000{col 59}{space 4} .4484892{col 72}{space 3} .8385448
{txt}{space 6}state_fe_50 {c |}{col 19}{res}{space 2} .8927853{col 31}{space 2} .0521882{col 42}{space 1}   17.11{col 51}{space 3}0.000{col 59}{space 4}  .790251{col 72}{space 3} .9953195
{txt}{space 11}cong_1 {c |}{col 19}{res}{space 2}-.0460102{col 31}{space 2} .0263951{col 42}{space 1}   -1.74{col 51}{space 3}0.082{col 59}{space 4}-.0978687{col 72}{space 3} .0058483
{txt}{space 11}cong_2 {c |}{col 19}{res}{space 2}-.0144582{col 31}{space 2} .0248542{col 42}{space 1}   -0.58{col 51}{space 3}0.561{col 59}{space 4}-.0632893{col 72}{space 3} .0343728
{txt}{space 11}cong_3 {c |}{col 19}{res}{space 2}-.0148353{col 31}{space 2} .0213255{col 42}{space 1}   -0.70{col 51}{space 3}0.487{col 59}{space 4}-.0567334{col 72}{space 3} .0270628
{txt}{space 11}cong_4 {c |}{col 19}{res}{space 2}        0{col 31}{txt}  (omitted)
{space 11}cong_5 {c |}{col 19}{res}{space 2} .0302558{col 31}{space 2} .0366766{col 42}{space 1}    0.82{col 51}{space 3}0.410{col 59}{space 4}-.0418028{col 72}{space 3} .1023144
{txt}{space 12}_cons {c |}{col 19}{res}{space 2}-.2458795{col 31}{space 2} .1722415{col 42}{space 1}   -1.43{col 51}{space 3}0.154{col 59}{space 4}-.5842826{col 72}{space 3} .0925235
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. *Column 3
. *Standardized coefficients
. regress friend crop_Unit career prop_ag ln_ag_pac dist_povertypct dist_mednhhincome house_ag rep ideology female age state_fe_* cong_* if chamber_2==0, beta
{txt}note: state_fe_1 omitted because of collinearity
note: state_fe_11 omitted because of collinearity
note: state_fe_26 omitted because of collinearity
note: state_fe_28 omitted because of collinearity
note: state_fe_41 omitted because of collinearity
note: cong_4 omitted because of collinearity

      Source {c |}       SS           df       MS      Number of obs   ={res}     1,780
{txt}{hline 13}{c +}{hline 34}   F(60, 1719)     = {res}    18.64
{txt}       Model {c |} {res} 175.020767        60  2.91701278   {txt}Prob > F        ={res}    0.0000
{txt}    Residual {c |} {res} 269.080357     1,719  .156533076   {txt}R-squared       ={res}    0.3941
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    0.3730
{txt}       Total {c |} {res} 444.101124     1,779  .249635258   {txt}Root MSE        =   {res} .39564

{txt}{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}           friend{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 72}        Beta
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .2060763{col 31}{space 2} .0777575{col 42}{space 1}    2.65{col 51}{space 3}0.008{col 72}{space 3} .0628551
{txt}{space 11}career {c |}{col 19}{res}{space 2}  .207766{col 31}{space 2} .1127797{col 42}{space 1}    1.84{col 51}{space 3}0.066{col 72}{space 3} .0418313
{txt}{space 10}prop_ag {c |}{col 19}{res}{space 2} 1.764308{col 31}{space 2} .9869936{col 42}{space 1}    1.79{col 51}{space 3}0.074{col 72}{space 3} .0437648
{txt}{space 8}ln_ag_pac {c |}{col 19}{res}{space 2} .0165344{col 31}{space 2} .0036319{col 42}{space 1}    4.55{col 51}{space 3}0.000{col 72}{space 3} .0973616
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{res}{txt}
{com}. stdBeta
generate: 
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{res}{txt}{space 1}state_fe_38 {c |}{res} {ralign 12:.98224765}{txt} {space 1}{res} {ralign 12:.98224767}{txt} {space 1}{res} {ralign 12:.43311734}{txt} {space 1}
{res}{txt}{space 1}state_fe_39 {c |}{res} {ralign 12:.6001722}{txt} {space 1}{res} {ralign 12:.60017222}{txt} {space 1}{res} {ralign 12:.08522273}{txt} {space 1}
{res}{txt}{space 1}state_fe_40 {c |}{res} {ralign 12:.71114113}{txt} {space 1}{res} {ralign 12:.71114111}{txt} {space 1}{res} {ralign 12:.18624328}{txt} {space 1}
{res}{txt}{space 1}state_fe_41 {c |}{res} {ralign 12:(omitted)}{txt} {space 1}{res} {ralign 12:(omitted)}{txt} {space 1}{res} {ralign 12:(omitted)}{txt} {space 1}
{res}{txt}{space 1}state_fe_42 {c |}{res} {ralign 12:.99220351}{txt} {space 1}{res} {ralign 12:.99220349}{txt} {space 1}{res} {ralign 12:.30498883}{txt} {space 1}
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{res}{txt}{space 1}state_fe_48 {c |}{res} {ralign 12:.68743145}{txt} {space 1}{res} {ralign 12:.68743145}{txt} {space 1}{res} {ralign 12:.20889497}{txt} {space 1}
{res}{txt}{space 1}state_fe_49 {c |}{res} {ralign 12:.64351701}{txt} {space 1}{res} {ralign 12:.64351703}{txt} {space 1}{res} {ralign 12:.11380687}{txt} {space 1}
{res}{txt}{space 1}state_fe_50 {c |}{res} {ralign 12:.89278528}{txt} {space 1}{res} {ralign 12:.89278528}{txt} {space 1}{res} {ralign 12:.09459762}{txt} {space 1}
{res}{txt}{space 6}cong_1 {c |}{res} {ralign 12:-.04601021}{txt} {space 1}{res} {ralign 12:(omitted)}{txt} {space 1}{res} {ralign 12:-.03567057}{txt} {space 1}
{res}{txt}{space 6}cong_2 {c |}{res} {ralign 12:-.01445823}{txt} {space 1}{res} {ralign 12:.03155198}{txt} {space 1}{res} {ralign 12:-.01168662}{txt} {space 1}
{res}{txt}{space 6}cong_3 {c |}{res} {ralign 12:-.01483529}{txt} {space 1}{res} {ralign 12:.03117492}{txt} {space 1}{res} {ralign 12:-.01197919}{txt} {space 1}
{res}{txt}{space 6}cong_4 {c |}{res} {ralign 12:(omitted)}{txt} {space 1}{res} {ralign 12:.04601021}{txt} {space 1}{res} {ralign 12:(omitted)}{txt} {space 1}
{res}{txt}{space 6}cong_5 {c |}{res} {ralign 12:.03025582}{txt} {space 1}{res} {ralign 12:.07626603}{txt} {space 1}{res} {ralign 12:.02443094}{txt} {space 1}
{res}{txt}{space 7}_cons {c |}{res} {ralign 12:-.24587954}{txt} {space 1}{res} {ralign 12:-.00930544}{txt} {space 1}{res} {ralign 12:-3.214e-08}{txt} {space 1}
{res}{txt}{hline 12}{c -}{c BT}{c -}{hline 12}{c -}{c -}{c -}{hline 12}{c -}{c -}{c -}{hline 12}{c -}{c -}
{res}{txt}
{com}. 
. clear
{txt}
{com}. 
. *Agriculture Protection Ideal Point Models
. 
. *Select directory
. use "AgricultureData_Ideal.dta"
{txt}
{com}. 
. *FINAL MODELS:
. *Normalized (to unit interval) croplandharvested_acres
. sum croplandharvested_acres

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
croplandha~s {c |}{res}        780    73806.54     91125.1          0     600848
{txt}
{com}. return list

{txt}scalars:
                  r(N) =  {res}780
              {txt}r(sum_w) =  {res}780
               {txt}r(mean) =  {res}73806.54487179487
                {txt}r(Var) =  {res}8303782952.718139
                 {txt}r(sd) =  {res}91125.09507659313
                {txt}r(min) =  {res}0
                {txt}r(max) =  {res}600848
                {txt}r(sum) =  {res}57569105
{txt}
{com}. gen cropmean=r(mean)
{txt}
{com}. gen cropsd=r(sd)
{txt}
{com}. gen standcrop=(croplandharvested_acres-cropmean)/cropsd
{txt}
{com}. gen cropmax=r(max)
{txt}
{com}. gen cropmin=0
{txt}
{com}. gen crop_Unit=1/cropmax*(croplandharvested_acres-cropmax)+1
{txt}
{com}. 
. *Column 4
. regress AgIdeal_Unit crop_Unit career dist_povertypct dist_mednhhincome house_ag rep ideology female age i.state_icpsr i.TimeNum, vce(cluster icpsr_id)

{txt}Linear regression                               Number of obs     = {res}       780
                                                {txt}{help j_robustsingular:F(51, 496) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3081
                                                {txt}Root MSE          =    {res} .18364

{txt}{ralign 83:(Std. Err. adjusted for {res:497} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}     AgIdeal_Unit{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .1407861{col 31}{space 2}  .052658{col 42}{space 1}    2.67{col 51}{space 3}0.008{col 59}{space 4} .0373259{col 72}{space 3} .2442463
{txt}{space 11}career {c |}{col 19}{res}{space 2} .0923267{col 31}{space 2} .0856376{col 42}{space 1}    1.08{col 51}{space 3}0.282{col 59}{space 4}-.0759305{col 72}{space 3} .2605838
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2}-.4051304{col 31}{space 2} .2728812{col 42}{space 1}   -1.48{col 51}{space 3}0.138{col 59}{space 4} -.941276{col 72}{space 3} .1310153
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0041971{col 31}{space 2} .0011793{col 42}{space 1}   -3.56{col 51}{space 3}0.000{col 59}{space 4}-.0065142{col 72}{space 3}-.0018801
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0581334{col 31}{space 2} .0192264{col 42}{space 1}    3.02{col 51}{space 3}0.003{col 59}{space 4} .0203582{col 72}{space 3} .0959087
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2}-.1479692{col 31}{space 2} .0153516{col 42}{space 1}   -9.64{col 51}{space 3}0.000{col 59}{space 4}-.1781314{col 72}{space 3} -.117807
{txt}{space 9}ideology {c |}{col 19}{res}{space 2} .1681619{col 31}{space 2} .1412497{col 42}{space 1}    1.19{col 51}{space 3}0.234{col 59}{space 4}-.1093597{col 72}{space 3} .4456835
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0091247{col 31}{space 2} .0162651{col 42}{space 1}   -0.56{col 51}{space 3}0.575{col 59}{space 4}-.0410816{col 72}{space 3} .0228322
{txt}{space 14}age {c |}{col 19}{res}{space 2} .0006005{col 31}{space 2} .0006216{col 42}{space 1}    0.97{col 51}{space 3}0.335{col 59}{space 4}-.0006209{col 72}{space 3} .0018219
{txt}{space 17} {c |}
{space 6}state_icpsr {c |}
{space 15}2  {c |}{col 19}{res}{space 2}-.0710138{col 31}{space 2} .0471028{col 42}{space 1}   -1.51{col 51}{space 3}0.132{col 59}{space 4}-.1635595{col 72}{space 3} .0215319
{txt}{space 15}3  {c |}{col 19}{res}{space 2}-.0676769{col 31}{space 2} .0473616{col 42}{space 1}   -1.43{col 51}{space 3}0.154{col 59}{space 4} -.160731{col 72}{space 3} .0253772
{txt}{space 15}4  {c |}{col 19}{res}{space 2} .0517992{col 31}{space 2} .0415276{col 42}{space 1}    1.25{col 51}{space 3}0.213{col 59}{space 4}-.0297925{col 72}{space 3} .1333909
{txt}{space 15}5  {c |}{col 19}{res}{space 2}-.0659286{col 31}{space 2} .0846946{col 42}{space 1}   -0.78{col 51}{space 3}0.437{col 59}{space 4}-.2323329{col 72}{space 3} .1004758
{txt}{space 15}6  {c |}{col 19}{res}{space 2}-.0401299{col 31}{space 2} .0453304{col 42}{space 1}   -0.89{col 51}{space 3}0.376{col 59}{space 4}-.1291932{col 72}{space 3} .0489333
{txt}{space 14}11  {c |}{col 19}{res}{space 2}-.0493679{col 31}{space 2} .0361897{col 42}{space 1}   -1.36{col 51}{space 3}0.173{col 59}{space 4}-.1204719{col 72}{space 3} .0217362
{txt}{space 14}12  {c |}{col 19}{res}{space 2}-.0553624{col 31}{space 2} .0443159{col 42}{space 1}   -1.25{col 51}{space 3}0.212{col 59}{space 4}-.1424325{col 72}{space 3} .0317078
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{txt}{space 17} {c |}
{space 8}1.TimeNum {c |}{col 19}{res}{space 2}-.0342242{col 31}{space 2} .0148351{col 42}{space 1}   -2.31{col 51}{space 3}0.021{col 59}{space 4}-.0633716{col 72}{space 3}-.0050768
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{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *Column 5
. regress AgIdeal_Unit crop_Unit prop_ag dist_povertypct dist_mednhhincome house_ag rep ideology female age i.state_icpsr i.TimeNum, vce(cluster icpsr_id)

{txt}Linear regression                               Number of obs     = {res}       780
                                                {txt}{help j_robustsingular:F(51, 496) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3108
                                                {txt}Root MSE          =    {res} .18327

{txt}{ralign 83:(Std. Err. adjusted for {res:497} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}     AgIdeal_Unit{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .1291626{col 31}{space 2} .0549558{col 42}{space 1}    2.35{col 51}{space 3}0.019{col 59}{space 4} .0211878{col 72}{space 3} .2371374
{txt}{space 10}prop_ag {c |}{col 19}{res}{space 2} 1.451669{col 31}{space 2} 1.374761{col 42}{space 1}    1.06{col 51}{space 3}0.292{col 59}{space 4}-1.249404{col 72}{space 3} 4.152742
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2}-.4660113{col 31}{space 2} .2640767{col 42}{space 1}   -1.76{col 51}{space 3}0.078{col 59}{space 4}-.9848582{col 72}{space 3} .0528357
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0040206{col 31}{space 2} .0012583{col 42}{space 1}   -3.20{col 51}{space 3}0.001{col 59}{space 4}-.0064928{col 72}{space 3}-.0015484
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0536246{col 31}{space 2} .0201354{col 42}{space 1}    2.66{col 51}{space 3}0.008{col 59}{space 4} .0140634{col 72}{space 3} .0931858
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2}-.1473219{col 31}{space 2} .0153278{col 42}{space 1}   -9.61{col 51}{space 3}0.000{col 59}{space 4}-.1774373{col 72}{space 3}-.1172065
{txt}{space 9}ideology {c |}{col 19}{res}{space 2} .2139812{col 31}{space 2} .1388489{col 42}{space 1}    1.54{col 51}{space 3}0.124{col 59}{space 4}-.0588234{col 72}{space 3} .4867857
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0075444{col 31}{space 2} .0162029{col 42}{space 1}   -0.47{col 51}{space 3}0.642{col 59}{space 4}-.0393792{col 72}{space 3} .0242904
{txt}{space 14}age {c |}{col 19}{res}{space 2} .0006709{col 31}{space 2} .0006157{col 42}{space 1}    1.09{col 51}{space 3}0.276{col 59}{space 4}-.0005388{col 72}{space 3} .0018805
{txt}{space 17} {c |}
{space 6}state_icpsr {c |}
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{txt}{space 17} {c |}
{space 8}1.TimeNum {c |}{col 19}{res}{space 2}-.0344821{col 31}{space 2} .0149119{col 42}{space 1}   -2.31{col 51}{space 3}0.021{col 59}{space 4}-.0637804{col 72}{space 3}-.0051838
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7313598{col 31}{space 2} .1011942{col 42}{space 1}    7.23{col 51}{space 3}0.000{col 59}{space 4} .5325376{col 72}{space 3} .9301821
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *Column 6
. regress AgIdeal_Unit crop_Unit ln_ag_pac dist_povertypct dist_mednhhincome house_ag rep ideology female age i.state_icpsr i.TimeNum, vce(cluster icpsr_id)

{txt}Linear regression                               Number of obs     = {res}       780
                                                {txt}{help j_robustsingular:F(51, 496) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3173
                                                {txt}Root MSE          =    {res}  .1824

{txt}{ralign 83:(Std. Err. adjusted for {res:497} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}     AgIdeal_Unit{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .1456049{col 31}{space 2} .0552451{col 42}{space 1}    2.64{col 51}{space 3}0.009{col 59}{space 4} .0370615{col 72}{space 3} .2541482
{txt}{space 8}ln_ag_pac {c |}{col 19}{res}{space 2} .0087061{col 31}{space 2} .0026431{col 42}{space 1}    3.29{col 51}{space 3}0.001{col 59}{space 4} .0035131{col 72}{space 3} .0138992
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2}-.4125386{col 31}{space 2} .2652424{col 42}{space 1}   -1.56{col 51}{space 3}0.121{col 59}{space 4}-.9336757{col 72}{space 3} .1085986
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0039968{col 31}{space 2} .0011718{col 42}{space 1}   -3.41{col 51}{space 3}0.001{col 59}{space 4}-.0062991{col 72}{space 3}-.0016944
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0537542{col 31}{space 2} .0195394{col 42}{space 1}    2.75{col 51}{space 3}0.006{col 59}{space 4}  .015364{col 72}{space 3} .0921444
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2}-.1561032{col 31}{space 2} .0154615{col 42}{space 1}  -10.10{col 51}{space 3}0.000{col 59}{space 4}-.1864813{col 72}{space 3}-.1257251
{txt}{space 9}ideology {c |}{col 19}{res}{space 2}  .192207{col 31}{space 2} .1385359{col 42}{space 1}    1.39{col 51}{space 3}0.166{col 59}{space 4}-.0799825{col 72}{space 3} .4643964
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0074581{col 31}{space 2} .0162409{col 42}{space 1}   -0.46{col 51}{space 3}0.646{col 59}{space 4}-.0393676{col 72}{space 3} .0244513
{txt}{space 14}age {c |}{col 19}{res}{space 2} .0005058{col 31}{space 2} .0006251{col 42}{space 1}    0.81{col 51}{space 3}0.419{col 59}{space 4}-.0007223{col 72}{space 3} .0017339
{txt}{space 17} {c |}
{space 6}state_icpsr {c |}
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{txt}{space 15}3  {c |}{col 19}{res}{space 2}-.0517817{col 31}{space 2} .0453847{col 42}{space 1}   -1.14{col 51}{space 3}0.254{col 59}{space 4}-.1409517{col 72}{space 3} .0373883
{txt}{space 15}4  {c |}{col 19}{res}{space 2} .0688277{col 31}{space 2} .0487514{col 42}{space 1}    1.41{col 51}{space 3}0.159{col 59}{space 4} -.026957{col 72}{space 3} .1646125
{txt}{space 15}5  {c |}{col 19}{res}{space 2}-.0482601{col 31}{space 2} .0680179{col 42}{space 1}   -0.71{col 51}{space 3}0.478{col 59}{space 4}-.1818988{col 72}{space 3} .0853786
{txt}{space 15}6  {c |}{col 19}{res}{space 2}-.0067764{col 31}{space 2} .0383998{col 42}{space 1}   -0.18{col 51}{space 3}0.860{col 59}{space 4}-.0822228{col 72}{space 3} .0686699
{txt}{space 14}11  {c |}{col 19}{res}{space 2}-.0534136{col 31}{space 2} .0347469{col 42}{space 1}   -1.54{col 51}{space 3}0.125{col 59}{space 4}-.1216828{col 72}{space 3} .0148557
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{txt}{space 14}71  {c |}{col 19}{res}{space 2}-.0433852{col 31}{space 2}  .039061{col 42}{space 1}   -1.11{col 51}{space 3}0.267{col 59}{space 4}-.1201306{col 72}{space 3} .0333602
{txt}{space 14}72  {c |}{col 19}{res}{space 2}-.0607989{col 31}{space 2} .1158646{col 42}{space 1}   -0.52{col 51}{space 3}0.600{col 59}{space 4}-.2884449{col 72}{space 3} .1668471
{txt}{space 14}73  {c |}{col 19}{res}{space 2}-.0064711{col 31}{space 2} .0576957{col 42}{space 1}   -0.11{col 51}{space 3}0.911{col 59}{space 4}-.1198292{col 72}{space 3}  .106887
{txt}{space 17} {c |}
{space 8}1.TimeNum {c |}{col 19}{res}{space 2}-.0345246{col 31}{space 2} .0149299{col 42}{space 1}   -2.31{col 51}{space 3}0.021{col 59}{space 4}-.0638582{col 72}{space 3} -.005191
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7496032{col 31}{space 2} .0943875{col 42}{space 1}    7.94{col 51}{space 3}0.000{col 59}{space 4} .5641545{col 72}{space 3} .9350519
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. *Column 7
. regress AgIdeal_Unit crop_Unit career prop_ag ln_ag_pac dist_povertypct dist_mednhhincome house_ag rep ideology female age i.state_icpsr i.TimeNum, vce(cluster icpsr_id)

{txt}Linear regression                               Number of obs     = {res}       780
                                                {txt}{help j_robustsingular:F(53, 496) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.3203
                                                {txt}Root MSE          =    {res} .18226

{txt}{ralign 83:(Std. Err. adjusted for {res:497} clusters in icpsr_id)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}     AgIdeal_Unit{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}crop_Unit {c |}{col 19}{res}{space 2} .1205726{col 31}{space 2} .0512845{col 42}{space 1}    2.35{col 51}{space 3}0.019{col 59}{space 4}  .019811{col 72}{space 3} .2213343
{txt}{space 11}career {c |}{col 19}{res}{space 2} .0346432{col 31}{space 2} .0824516{col 42}{space 1}    0.42{col 51}{space 3}0.675{col 59}{space 4}-.1273544{col 72}{space 3} .1966407
{txt}{space 10}prop_ag {c |}{col 19}{res}{space 2} 1.133306{col 31}{space 2}  1.29558{col 42}{space 1}    0.87{col 51}{space 3}0.382{col 59}{space 4}-1.412195{col 72}{space 3} 3.678807
{txt}{space 8}ln_ag_pac {c |}{col 19}{res}{space 2}  .008089{col 31}{space 2} .0027101{col 42}{space 1}    2.98{col 51}{space 3}0.003{col 59}{space 4} .0027643{col 72}{space 3} .0134138
{txt}{space 2}dist_povertypct {c |}{col 19}{res}{space 2} -.469663{col 31}{space 2} .2596189{col 42}{space 1}   -1.81{col 51}{space 3}0.071{col 59}{space 4}-.9797514{col 72}{space 3} .0404254
{txt}dist_mednhhincome {c |}{col 19}{res}{space 2}-.0038554{col 31}{space 2} .0012465{col 42}{space 1}   -3.09{col 51}{space 3}0.002{col 59}{space 4}-.0063045{col 72}{space 3}-.0014062
{txt}{space 9}house_ag {c |}{col 19}{res}{space 2} .0451089{col 31}{space 2} .0205484{col 42}{space 1}    2.20{col 51}{space 3}0.029{col 59}{space 4} .0047362{col 72}{space 3} .0854816
{txt}{space 3}republican_ind {c |}{col 19}{res}{space 2}-.1550419{col 31}{space 2} .0153796{col 42}{space 1}  -10.08{col 51}{space 3}0.000{col 59}{space 4}-.1852591{col 72}{space 3}-.1248248
{txt}{space 9}ideology {c |}{col 19}{res}{space 2} .2310169{col 31}{space 2} .1360098{col 42}{space 1}    1.70{col 51}{space 3}0.090{col 59}{space 4}-.0362095{col 72}{space 3} .4982434
{txt}{space 7}female_ind {c |}{col 19}{res}{space 2}-.0053551{col 31}{space 2} .0161174{col 42}{space 1}   -0.33{col 51}{space 3}0.740{col 59}{space 4}-.0370219{col 72}{space 3} .0263117
{txt}{space 14}age {c |}{col 19}{res}{space 2} .0005423{col 31}{space 2} .0006188{col 42}{space 1}    0.88{col 51}{space 3}0.381{col 59}{space 4}-.0006734{col 72}{space 3} .0017581
{txt}{space 17} {c |}
{space 6}state_icpsr {c |}
{space 15}2  {c |}{col 19}{res}{space 2}-.0898347{col 31}{space 2} .0481705{col 42}{space 1}   -1.86{col 51}{space 3}0.063{col 59}{space 4}-.1844781{col 72}{space 3} .0048086
{txt}{space 15}3  {c |}{col 19}{res}{space 2}-.0530034{col 31}{space 2} .0457668{col 42}{space 1}   -1.16{col 51}{space 3}0.247{col 59}{space 4} -.142924{col 72}{space 3} .0369173
{txt}{space 15}4  {c |}{col 19}{res}{space 2} .0663457{col 31}{space 2} .0479694{col 42}{space 1}    1.38{col 51}{space 3}0.167{col 59}{space 4}-.0279027{col 72}{space 3} .1605941
{txt}{space 15}5  {c |}{col 19}{res}{space 2}-.0466136{col 31}{space 2} .0702605{col 42}{space 1}   -0.66{col 51}{space 3}0.507{col 59}{space 4}-.1846586{col 72}{space 3} .0914313
{txt}{space 15}6  {c |}{col 19}{res}{space 2}-.0191464{col 31}{space 2} .0401042{col 42}{space 1}   -0.48{col 51}{space 3}0.633{col 59}{space 4}-.0979415{col 72}{space 3} .0596488
{txt}{space 14}11  {c |}{col 19}{res}{space 2}-.0532921{col 31}{space 2} .0348758{col 42}{space 1}   -1.53{col 51}{space 3}0.127{col 59}{space 4}-.1218146{col 72}{space 3} .0152304
{txt}{space 14}12  {c |}{col 19}{res}{space 2}-.0481674{col 31}{space 2} .0446151{col 42}{space 1}   -1.08{col 51}{space 3}0.281{col 59}{space 4}-.1358252{col 72}{space 3} .0394905
{txt}{space 14}13  {c |}{col 19}{res}{space 2} .0381493{col 31}{space 2} .0362606{col 42}{space 1}    1.05{col 51}{space 3}0.293{col 59}{space 4} -.033094{col 72}{space 3} .1093927
{txt}{space 14}14  {c |}{col 19}{res}{space 2} .0190201{col 31}{space 2} .0381114{col 42}{space 1}    0.50{col 51}{space 3}0.618{col 59}{space 4}-.0558597{col 72}{space 3} .0938998
{txt}{space 14}21  {c |}{col 19}{res}{space 2}-.0817365{col 31}{space 2} .0420365{col 42}{space 1}   -1.94{col 51}{space 3}0.052{col 59}{space 4}-.1643281{col 72}{space 3}  .000855
{txt}{space 14}22  {c |}{col 19}{res}{space 2}-.0162101{col 31}{space 2} .0428251{col 42}{space 1}   -0.38{col 51}{space 3}0.705{col 59}{space 4} -.100351{col 72}{space 3} .0679308
{txt}{space 14}23  {c |}{col 19}{res}{space 2} .0137898{col 31}{space 2} .0449816{col 42}{space 1}    0.31{col 51}{space 3}0.759{col 59}{space 4} -.074588{col 72}{space 3} .1021677
{txt}{space 14}24  {c |}{col 19}{res}{space 2}-.1130152{col 31}{space 2} .0408884{col 42}{space 1}   -2.76{col 51}{space 3}0.006{col 59}{space 4} -.193351{col 72}{space 3}-.0326794
{txt}{space 14}25  {c |}{col 19}{res}{space 2}-.2684152{col 31}{space 2} .0507576{col 42}{space 1}   -5.29{col 51}{space 3}0.000{col 59}{space 4}-.3681417{col 72}{space 3}-.1686887
{txt}{space 14}31  {c |}{col 19}{res}{space 2}-.0888384{col 31}{space 2} .0635523{col 42}{space 1}   -1.40{col 51}{space 3}0.163{col 59}{space 4}-.2137032{col 72}{space 3} .0360265
{txt}{space 14}32  {c |}{col 19}{res}{space 2}-.0939965{col 31}{space 2} .0622293{col 42}{space 1}   -1.51{col 51}{space 3}0.132{col 59}{space 4} -.216262{col 72}{space 3}  .028269
{txt}{space 14}33  {c |}{col 19}{res}{space 2} .0246782{col 31}{space 2} .0388532{col 42}{space 1}    0.64{col 51}{space 3}0.526{col 59}{space 4}-.0516589{col 72}{space 3} .1010154
{txt}{space 14}34  {c |}{col 19}{res}{space 2} .1061342{col 31}{space 2} .0413004{col 42}{space 1}    2.57{col 51}{space 3}0.010{col 59}{space 4} .0249889{col 72}{space 3} .1872794
{txt}{space 14}35  {c |}{col 19}{res}{space 2}-.0040514{col 31}{space 2} .0751279{col 42}{space 1}   -0.05{col 51}{space 3}0.957{col 59}{space 4}-.1516595{col 72}{space 3} .1435567
{txt}{space 14}40  {c |}{col 19}{res}{space 2} .0227583{col 31}{space 2} .0544836{col 42}{space 1}    0.42{col 51}{space 3}0.676{col 59}{space 4}-.0842889{col 72}{space 3} .1298054
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{txt}{space 14}42  {c |}{col 19}{res}{space 2} .0914236{col 31}{space 2} .0467176{col 42}{space 1}    1.96{col 51}{space 3}0.051{col 59}{space 4}-.0003653{col 72}{space 3} .1832124
{txt}{space 14}43  {c |}{col 19}{res}{space 2}-.0212374{col 31}{space 2} .0428172{col 42}{space 1}   -0.50{col 51}{space 3}0.620{col 59}{space 4}-.1053628{col 72}{space 3} .0628879
{txt}{space 14}44  {c |}{col 19}{res}{space 2} .0200041{col 31}{space 2} .0545371{col 42}{space 1}    0.37{col 51}{space 3}0.714{col 59}{space 4}-.0871482{col 72}{space 3} .1271564
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{txt}{space 14}62  {c |}{col 19}{res}{space 2}-.0343577{col 31}{space 2} .0519881{col 42}{space 1}   -0.66{col 51}{space 3}0.509{col 59}{space 4}-.1365019{col 72}{space 3} .0677864
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{txt}{space 17} {c |}
{space 8}1.TimeNum {c |}{col 19}{res}{space 2}-.0341719{col 31}{space 2} .0149023{col 42}{space 1}   -2.29{col 51}{space 3}0.022{col 59}{space 4}-.0634513{col 72}{space 3}-.0048924
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .7210436{col 31}{space 2} .0998218{col 42}{space 1}    7.22{col 51}{space 3}0.000{col 59}{space 4} .5249179{col 72}{space 3} .9171694
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
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{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/rvwielen/Library/CloudStorage/Dropbox/HouseBirthplaceProject/Paper/PSRM/FINAL_ReplicationMaterials/ReplicationMaterials_Submitted/ReplicationLog_Final.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 5 Aug 2024, 07:18:50
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